d365fo-client

A comprehensive Python client library and MCP server for Microsoft Dynamics 365 Finance & Operations (D365 F&O) that provides easy access to OData endpoints, metadata operations, label management, and AI assistant integration.

13 stars PythonDeveloper Kits Updated Oct 19, 2025

d365fod365toolsmcp-serverpython

Documentation

Dynamics 365 Finance & Operations MCP Server

Production-ready Model Context Protocol (MCP) server that exposes the full capabilities of Microsoft Dynamics 365 Finance & Operations (D365 F&O) to AI assistants and other MCP-compatible tools. This enables sophisticated Dynamics 365 integration workflows through standardized protocol interactions.

🚀 One-Click Installation for VS Code:

🐳 Docker Installation for VS Code:

☁️ Deploy to Azure Container Apps:

Deploy the MCP server as a secure, internet-accessible HTTP endpoint with OAuth or API Key authentication. Perfect for web integrations and remote AI assistant access.

Option 1: Using Bash Script (Recommended)

bash

# Download and run the deployment script
curl -O https://raw.githubusercontent.com/mafzaal/d365fo-client/main/deploy-aca.sh
chmod +x deploy-aca.sh

# Set authentication (choose OAuth or API Key)
export D365FO_MCP_AUTH_CLIENT_ID="your-client-id"
export D365FO_MCP_AUTH_CLIENT_SECRET="your-client-secret"
export D365FO_MCP_AUTH_TENANT_ID="your-tenant-id"
# OR
export D365FO_MCP_API_KEY_VALUE="your-secret-key"

# Deploy
./deploy-aca.sh

Option 2: Using ARM Template

1. Download azure-deploy.json

2. Go to Azure Portal → Deploy a custom template

3. Click "Build your own template in the editor"

4. Paste the contents of `azure-deploy.json`

5. Fill in the parameters and deploy

Also includes a comprehensive Python client library for Microsoft Dynamics 365 Finance & Operations with OData endpoints, metadata operations, label management, and CLI tools.

MCP Server Overview

The d365fo-client includes a production-ready Model Context Protocol (MCP) server (`d365fo-fastmcp-server`) built on the FastMCP framework that exposes the full capabilities of D365 Finance & Operations to AI assistants and other MCP-compatible tools.

The server provides multi-transport support (stdio, HTTP, SSE) with enhanced performance and deployment flexibility.

Key Features

49 comprehensive tools covering all major D365 F&O operations across 9 functional categories
12 resource types with comprehensive metadata exposure and discovery capabilities
2 prompt templates for advanced workflow assistance
Multi-transport support (FastMCP): stdio, HTTP, Server-Sent Events (SSE)
Production-ready implementation with proper error handling, authentication, and security validation
Enhanced performance (FastMCP): 40% faster startup, 15% lower memory usage
Advanced profile management supporting multiple environments with secure credential storage
Database analysis capabilities with secure SQL querying and metadata insights
Session-based synchronization with detailed progress tracking and multiple sync strategies
Multi-language support with label resolution and localization capabilities
Enterprise security with Azure AD integration, Key Vault support, and audit logging

New in v0.3.0

🔧 Pydantic Settings Model: Type-safe environment variable management with validation for 35+ configuration options
📂 Custom Log File Support: `D365FO_LOG_FILE` environment variable for flexible log file paths
🔄 Legacy Config Migration: Automatic detection and migration of legacy configuration files
🌐 Environment Variable Standardization: All MCP HTTP variables now use `D365FO_` prefix for consistency
⚡ Enhanced FastMCP Server: Improved startup configuration, error handling, and graceful shutdown
🔀 MCP Return Type Standardization: All MCP tools now return dictionaries instead of JSON strings for better type safety
🛠️ Enhanced Configuration: Support for `.env` files and comprehensive environment variable documentation

Quick Start

Installation and Setup

bash

# Install d365fo-client with MCP dependencies
pip install d365fo-client

# Set up environment variables
export D365FO_BASE_URL="https://your-environment.dynamics.com"
export D365FO_CLIENT_ID="your-client-id"          # Optional with default credentials
export D365FO_CLIENT_SECRET="your-client-secret"  # Optional with default credentials  
export D365FO_TENANT_ID="your-tenant-id"          # Optional with default credentials

FastMCP Server (Recommended)

The modern FastMCP implementation provides enhanced performance and multiple transport options:

bash

# Development (stdio transport - default)
d365fo-fastmcp-server

# Production HTTP API
d365fo-fastmcp-server --transport http --port 8000 --host 0.0.0.0

# Real-time Web Applications (SSE)
d365fo-fastmcp-server --transport sse --port 8001 --host 0.0.0.0

Key Benefits:

Optimized performance with FastMCP framework
Efficient resource usage through optimized architecture
Multi-transport support: stdio, HTTP, Server-Sent Events (SSE)
Enhanced error handling with better async/await support
Production ready with web transports for API integration

Integration with AI Assistants

VS Code Integration (Recommended)

FastMCP Server with Default Credentials:

Add to your VS Code `mcp.json` for GitHub Copilot with MCP:

json

{
  "servers": {
    "d365fo-fastmcp-server": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "--from",
        "d365fo-client@latest",
        "d365fo-fastmcp-server"
      ],
      "env": {
        "D365FO_BASE_URL": "https://your-environment.dynamics.com",
        "D365FO_LOG_LEVEL": "INFO"
      }
    }
  }
}

Option 2: Explicit Credentials

For environments requiring service principal authentication:

json

{
  "servers": {
    "d365fo-fastmcp-server": {
      "type": "stdio", 
      "command": "uvx",
      "args": [
        "--from",
        "d365fo-client",
        "d365fo-fastmcp-server"
      ],
      "env": {
        "D365FO_BASE_URL": "https://your-environment.dynamics.com",
        "D365FO_LOG_LEVEL": "DEBUG",
        "D365FO_CLIENT_ID": "${input:client_id}",
        "D365FO_CLIENT_SECRET": "${input:client_secret}",
        "D365FO_TENANT_ID": "${input:tenant_id}"
      }
    }
  },
  "inputs": [
    {
      "id": "tenant_id",
      "type": "promptString",
      "description": "Azure AD Tenant ID for D365 F&O authentication",
      "password": true
    },
    {
      "id": "client_id", 
      "type": "promptString",
      "description": "Azure AD Client ID for D365 F&O authentication",
      "password": true
    },
    {
      "id": "client_secret",
      "type": "promptString", 
      "description": "Azure AD Client Secret for D365 F&O authentication",
      "password": true
    }
  ]
}

Option 3: Docker Integration

For containerized environments and enhanced isolation:

json

{
  "servers": {
    "d365fo-fastmcp-server": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-v",
        "d365fo-mcp:/home/mcp_user/",
        "-e",
        "D365FO_CLIENT_ID=${input:client_id}",
        "-e",
        "D365FO_CLIENT_SECRET=${input:client_secret}",
        "-e",
        "D365FO_TENANT_ID=${input:tenant_id}",
        "ghcr.io/mafzaal/d365fo-client:latest"
      ],
      "env": {
        "D365FO_LOG_LEVEL": "DEBUG",
        "D365FO_CLIENT_ID": "${input:client_id}",
        "D365FO_CLIENT_SECRET": "${input:client_secret}",
        "D365FO_TENANT_ID": "${input:tenant_id}"
      }
    }
  },
  "inputs": [
    {
      "id": "tenant_id",
      "type": "promptString",
      "description": "Azure AD Tenant ID for D365 F&O authentication",
      "password": true
    },
    {
      "id": "client_id",
      "type": "promptString",
      "description": "Azure AD Client ID for D365 F&O authentication",
      "password": true
    },
    {
      "id": "client_secret",
      "type": "promptString",
      "description": "Azure AD Client Secret for D365 F&O authentication",
      "password": true
    }
  ]
}

Benefits of Docker approach:

Complete environment isolation and reproducibility
No local Python installation required
Consistent runtime environment across different systems
Automatic dependency management with pre-built image
Enhanced security through containerization
Persistent data storage via Docker volume (`d365fo-mcp`)

Prerequisites:

Docker installed and running
Access to Docker Hub or GitHub Container Registry
Network access for pulling the container image

Claude Desktop Integration

FastMCP Server:

Add to your Claude Desktop configuration:

json

{
  "mcpServers": {
    "d365fo-fastmcp": {
      "command": "uvx",
      "args": [
        "--from",
        "d365fo-client",
        "d365fo-fastmcp-server"
      ],
      "env": {
        "D365FO_BASE_URL": "https://your-environment.dynamics.com",
        "D365FO_LOG_LEVEL": "INFO"
      }
    }
  }
}

Traditional MCP Server (Alternative):

json

{
  "mcpServers": {
    "d365fo": {
      "command": "uvx",
      "args": [
        "--from",
        "d365fo-client",
        "d365fo-fastmcp-server"
      ],
      "env": {
        "D365FO_BASE_URL": "https://your-environment.dynamics.com",
        "D365FO_LOG_LEVEL": "INFO"
      }
    }
  }
}

Benefits of uvx approach:

Always uses the latest version from the repository
No local installation required
Automatic dependency management
Works across different environments

Web Integration with FastMCP

The FastMCP server provides HTTP and SSE transports for web application integration:

HTTP Transport for Web APIs

python

import aiohttp
import json

async def call_d365fo_api():
    """Example: Using HTTP transport for web API integration"""
    
    # Start FastMCP server with HTTP transport
    # d365fo-fastmcp-server --transport http --port 8000
    
    mcp_request = {
        "jsonrpc": "2.0",
        "id": 1,
        "method": "tools/call",
        "params": {
            "name": "d365fo_query_entities",
            "arguments": {
                "entityName": "CustomersV3",
                "top": 10,
                "select": ["CustomerAccount", "Name"]
            }
        }
    }
    
    async with aiohttp.ClientSession() as session:
        async with session.post(
            "http://localhost:8000/mcp",
            json=mcp_request,
            headers={"Content-Type": "application/json"}
        ) as response:
            result = await response.json()
            print(json.dumps(result, indent=2))

SSE Transport for Real-time Applications

javascript

// Example: JavaScript client for real-time D365FO data
// Start FastMCP server: d365fo-fastmcp-server --transport sse --port 8001

const eventSource = new EventSource('http://localhost:8001/sse');

eventSource.onmessage = function(event) {
    const data = JSON.parse(event.data);
    console.log('Received D365FO data:', data);
    
    // Handle real-time updates from D365FO
    if (data.method === 'notification') {
        updateDashboard(data.params);
    }
};

// Send MCP requests via SSE
function queryCustomers() {
    const request = {
        jsonrpc: "2.0",
        id: Date.now(),
        method: "tools/call",
        params: {
            name: "d365fo_search_entities",
            arguments: {
                pattern: "customer",
                limit: 50
            }
        }
    };
    
    fetch('http://localhost:8001/sse/send', {
        method: 'POST',
        headers: {'Content-Type': 'application/json'},
        body: JSON.stringify(request)
    });
}

Alternative: Programmatic Usage

python

from d365fo_client.mcp import D365FOMCPServer

# Create and run server with custom configuration
config = {
    "default_environment": {
        "base_url": "https://your-environment.dynamics.com",
        "use_default_credentials": True
    }
}

server = D365FOMCPServer(config)
await server.run()

Custom MCP Clients

Connect using any MCP-compatible client library:

python

from mcp import Client

async with Client("d365fo-fastmcp-server") as client:
    # Discover available tools
    tools = await client.list_tools()
    
    # Execute operations
    result = await client.call_tool(
        "d365fo_query_entities",
        {"entityName": "Customers", "top": 5}
    )

Docker Deployment

For containerized environments and production deployments:

Pull the Docker Image:

bash

# Pull from GitHub Container Registry
docker pull ghcr.io/mafzaal/d365fo-client:latest

# Or pull a specific version
docker pull ghcr.io/mafzaal/d365fo-client:v0.2.3

Standalone Docker Usage:

bash

# Run MCP server with environment variables
docker run --rm -i \
  -e D365FO_BASE_URL="https://your-environment.dynamics.com" \
  -e D365FO_CLIENT_ID="your-client-id" \
  -e D365FO_CLIENT_SECRET="your-client-secret" \
  -e D365FO_TENANT_ID="your-tenant-id" \
  -e D365FO_LOG_LEVEL="INFO" \
  -v d365fo-mcp:/home/mcp_user/ \
  ghcr.io/mafzaal/d365fo-client:latest

# Run CLI commands with Docker
docker run --rm -it \
  -e D365FO_BASE_URL="https://your-environment.dynamics.com" \
  -e D365FO_CLIENT_ID="your-client-id" \
  -e D365FO_CLIENT_SECRET="your-client-secret" \
  -e D365FO_TENANT_ID="your-tenant-id" \
  ghcr.io/mafzaal/d365fo-client:latest \
  d365fo-client entities --limit 10

Docker Compose Example:

yaml

version: '3.8'
services:
  d365fo-mcp:
    image: ghcr.io/mafzaal/d365fo-client:latest
    environment:
      - D365FO_BASE_URL=https://your-environment.dynamics.com
      - D365FO_CLIENT_ID=${D365FO_CLIENT_ID}
      - D365FO_CLIENT_SECRET=${D365FO_CLIENT_SECRET}
      - D365FO_TENANT_ID=${D365FO_TENANT_ID}
      - D365FO_LOG_LEVEL=INFO
    volumes:
      - d365fo-mcp:/home/mcp_user/
    stdin_open: true
    tty: true

volumes:
  d365fo-mcp:

Docker Benefits:

Complete environment isolation and reproducibility
No local Python installation required
Consistent runtime environment across different systems
Built-in dependency management
Enhanced security through containerization
Persistent data storage via Docker volumes
Easy integration with orchestration platforms (Kubernetes, Docker Swarm)

Architecture Benefits

For AI Assistants

Standardized Interface: Consistent MCP protocol access to D365 F&O
Rich Metadata: Self-describing entities and operations
Type Safety: Schema validation for all operations
Error Context: Detailed error information for troubleshooting

For Developers

Minimal Integration: Standard MCP client libraries
Comprehensive Coverage: Full D365 F&O functionality exposed
Performance Optimized: Efficient connection and caching strategies
Well Documented: Complete API documentation and examples

For Organizations

Secure Access: Enterprise-grade authentication (Azure AD, Managed Identity)
Audit Logging: Complete operation tracking and monitoring
Scalable Design: Connection pooling and session management
Maintenance Friendly: Clear architecture and comprehensive test coverage

Troubleshooting

Common Issues

Connection Failures

bash

# Test connectivity
d365fo-client version app --base-url https://your-environment.dynamics.com

# Check logs
tail -f ~/.d365fo-mcp/logs/mcp-server.log

Authentication Issues

bash

# Verify Azure CLI authentication
az account show

# Test with explicit credentials
export D365FO_CLIENT_ID="your-client-id"
# ... set other variables
d365fo-fastmcp-server

Performance Issues

bash

# Enable debug logging
export D365FO_LOG_LEVEL="DEBUG"

# Adjust connection settings
export D365FO_CONNECTION_TIMEOUT="120"
export D365FO_MAX_CONCURRENT_REQUESTS="5"

Getting Help

Logs: Check `~/.d365fo-mcp/logs/mcp-server.log` for detailed error information
Environment: Use `d365fo_get_environment_info` tool to check system status
Documentation: See MCP Implementation Summary for technical details
Issues: Report problems at GitHub Issues

MCP Tools

The server provides 49 comprehensive tools organized into functional categories:

Connection & Environment Tools (2 tools)

`d365fo_test_connection` - Test connectivity and authentication with performance metrics and error diagnostics
`d365fo_get_environment_info` - Get comprehensive environment details including versions, configurations, and capabilities

CRUD Operations Tools (7 tools)

`d365fo_query_entities` - Simplified OData querying with 'eq' filtering, wildcard patterns, field selection, and pagination
`d365fo_get_entity_record` - Retrieve specific records by key with expansion options and ETag support
`d365fo_create_entity_record` - Create new entity records with validation and business logic execution
`d365fo_update_entity_record` - Update existing records with partial updates and optimistic concurrency control
`d365fo_delete_entity_record` - Delete entity records with referential integrity checking and cascading rules
`d365fo_call_action` - Execute OData actions and functions for complex business operations
`d365fo_call_json_service` - Call generic JSON service endpoints with parameter support and response handling

Metadata Discovery Tools (6 tools)

`d365fo_search_entities` - Search entities by pattern with category filtering and full-text search capabilities
`d365fo_get_entity_schema` - Get detailed entity schemas with properties, relationships, and label resolution
`d365fo_search_actions` - Search available OData actions with binding type and parameter information
`d365fo_search_enumerations` - Search system enumerations with keyword-based filtering
`d365fo_get_enumeration_fields` - Get detailed enumeration member information with multi-language support
`d365fo_get_installed_modules` - Retrieve information about installed modules and their configurations

Label Management Tools (2 tools)

`d365fo_get_label` - Get single label text by ID with multi-language support and fallback options
`d365fo_get_labels_batch` - Get multiple labels efficiently with batch processing and performance optimization

Profile Management Tools (14 tools)

`d365fo_list_profiles` - List all configured D365FO environment profiles with status information
`d365fo_get_profile` - Get detailed configuration information for specific profiles
`d365fo_create_profile` - Create new environment profiles with comprehensive authentication options
`d365fo_update_profile` - Modify existing profile configurations with partial update support
`d365fo_delete_profile` - Remove environment profiles with proper cleanup and validation
`d365fo_set_default_profile` - Designate a specific profile as the default for operations
`d365fo_get_default_profile` - Retrieve information about the currently configured default profile
`d365fo_validate_profile` - Validate profile configurations for completeness and security compliance
`d365fo_test_profile_connection` - Test connectivity and authentication for specific profiles
`d365fo_clone_profile` - Clone existing profiles with customization options for new environments
`d365fo_search_profiles` - Search profiles by pattern with filtering and sorting capabilities
`d365fo_get_profile_names` - Get simplified list of available profile names for quick reference
`d365fo_import_profiles` - Import profile configurations from external sources or backups
`d365fo_export_profiles` - Export profile configurations for backup or deployment purposes

Database Analysis Tools (4 tools)

`d365fo_execute_sql_query` - Execute SELECT queries against metadata database with security validation
`d365fo_get_database_schema` - Get comprehensive database schema information including relationships
`d365fo_get_table_info` - Get detailed information about specific database tables with sample data
`d365fo_get_database_statistics` - Generate database statistics and analytics for performance monitoring

Synchronization Tools (5 tools)

`d365fo_start_sync` - Initiate metadata synchronization with various strategies and session tracking
`d365fo_get_sync_progress` - Monitor detailed progress of sync sessions with time estimates
`d365fo_cancel_sync` - Cancel running sync sessions with graceful cleanup
`d365fo_list_sync_sessions` - List all active sync sessions with status and progress information
`d365fo_get_sync_history` - Get history of completed sync sessions with success/failure status and statistics

SRS Reporting Tools (6 tools)

`d365fo_download_srs_report` - Download SQL Server Reporting Services (SRS) reports with parameter support
`d365fo_download_sales_confirmation` - Download sales confirmation reports in various formats
`d365fo_download_purchase_order` - Download purchase order documents with formatting options
`d365fo_download_customer_invoice` - Download customer invoice reports with customization
`d365fo_download_free_text_invoice` - Download free text invoice documents
`d365fo_download_debit_credit_note` - Download debit and credit note reports

Performance Monitoring Tools (3 tools)

`d365fo_get_server_performance` - Get server performance metrics and statistics
`d365fo_get_server_config` - Get server configuration information and system settings
`d365fo_reset_performance_stats` - Reset performance statistics and counters for fresh monitoring

**📖 For detailed information about all MCP tools including usage examples and best practices, see the Comprehensive MCP Tools Introduction.**

**🤖 For AI agents and assistants, see the AI Agent Guide for structured workflows, best practices, and automation patterns.**

MCP Resources

The server exposes four types of resources for discovery and access:

Entity Resources

Access entity metadata and sample data:

code

d365fo://entities/CustomersV3     # Customer entity with metadata and sample data
d365fo://entities/SalesOrders     # Sales order entity information
d365fo://entities/Products        # Product entity details

Metadata Resources

Access system-wide metadata:

code

d365fo://metadata/entities        # All data entities metadata (V2 cache)
d365fo://metadata/actions         # Available OData actions  
d365fo://metadata/enumerations    # System enumerations
d365fo://metadata/labels          # System labels and translations

Environment Resources

Access environment status and information:

code

d365fo://environment/status       # Environment health and connectivity
d365fo://environment/version      # Version information (app, platform, build)
d365fo://environment/cache        # Cache status and statistics V2

Query Resources

Access predefined and templated queries:

code

d365fo://queries/customers_recent # Recent customers query template
d365fo://queries/sales_summary    # Sales summary query with parameters

Database Resources (New in V2)

Access metadata database queries:

code

d365fo://database/entities        # SQL-based entity searches with FTS5
d365fo://database/actions         # Action discovery with metadata
d365fo://database/statistics      # Cache and performance statistics

Usage Examples

Basic Tool Execution

json

{
  "tool": "d365fo_query_entities",
  "arguments": {
    "entityName": "CustomersV3",
    "select": ["CustomerAccount", "Name", "Email"],
    "filter": "CustomerGroup eq 'VIP'",
    "top": 10
  }
}

Entity Schema Discovery

json

{
  "tool": "d365fo_get_entity_schema", 
  "arguments": {
    "entityName": "CustomersV3",
    "includeProperties": true,
    "resolveLabels": true,
    "language": "en-US"
  }
}

Environment Information

json

{
  "tool": "d365fo_get_environment_info",
  "arguments": {}
}

Authentication & Configuration

Default Credentials (Recommended)

Uses Azure Default Credential chain (Managed Identity, Azure CLI, etc.):

bash

export D365FO_BASE_URL="https://your-environment.dynamics.com"
# No additional auth environment variables needed
d365fo-fastmcp-server

Explicit Credentials

For service principal authentication:

bash

export D365FO_BASE_URL="https://your-environment.dynamics.com"
export D365FO_CLIENT_ID="your-client-id"
export D365FO_CLIENT_SECRET="your-client-secret"
export D365FO_TENANT_ID="your-tenant-id"
d365fo-fastmcp-server

Azure Key Vault Integration (New in v0.2.3)

For secure credential storage using Azure Key Vault:

bash

export D365FO_BASE_URL="https://your-environment.dynamics.com"
export D365FO_CREDENTIAL_SOURCE="keyvault"
export D365FO_KEYVAULT_URL="https://your-keyvault.vault.azure.net/"
d365fo-fastmcp-server

Advanced Configuration

New in v0.3.0: Comprehensive environment variable management with type safety and validation using Pydantic settings.

Create a configuration file or set additional environment variables:

bash

# === Core D365FO Connection Settings ===
export D365FO_BASE_URL="https://your-environment.dynamics.com"
export D365FO_CLIENT_ID="your-client-id"
export D365FO_CLIENT_SECRET="your-client-secret"
export D365FO_TENANT_ID="your-tenant-id"

# === Logging Configuration ===
export D365FO_LOG_LEVEL="DEBUG"                        # DEBUG, INFO, WARNING, ERROR, CRITICAL
export D365FO_LOG_FILE="/custom/path/server.log"       # Custom log file path

# === MCP Server Transport Settings (v0.3.0+) ===
export D365FO_MCP_TRANSPORT="stdio"                    # stdio, sse, http, streamable-http
export D365FO_MCP_HTTP_HOST="0.0.0.0"                 # HTTP host (default: 127.0.0.1)
export D365FO_MCP_HTTP_PORT="8000"                     # HTTP port (default: 8000)
export D365FO_MCP_HTTP_STATELESS="true"                # Enable stateless mode
export D365FO_MCP_HTTP_JSON="true"                     # Enable JSON response mode

# === Cache and Performance Settings ===
export D365FO_CACHE_DIR="/custom/cache/path"           # General cache directory
export D365FO_META_CACHE_DIR="/custom/metadata/cache"  # Metadata cache directory
export D365FO_LABEL_CACHE="true"                       # Enable label caching (default: true)
export D365FO_LABEL_EXPIRY="1440"                      # Label cache expiry in minutes (24 hours)
export D365FO_USE_CACHE_FIRST="true"                   # Use cache before API calls

# === Connection and Performance Tuning ===
export D365FO_TIMEOUT="60"                             # General timeout in seconds
export D365FO_MCP_MAX_CONCURRENT_REQUESTS="10"         # Max concurrent requests
export D365FO_MCP_REQUEST_TIMEOUT="30"                 # Request timeout in seconds
export D365FO_VERIFY_SSL="true"                        # Verify SSL certificates

# === MCP Authentication Settings (Advanced) ===
export D365FO_MCP_AUTH_CLIENT_ID="your-mcp-client-id"
export D365FO_MCP_AUTH_CLIENT_SECRET="your-mcp-client-secret"
export D365FO_MCP_AUTH_TENANT_ID="your-mcp-tenant-id"
export D365FO_MCP_AUTH_BASE_URL="http://localhost:8000"
export D365FO_MCP_AUTH_REQUIRED_SCOPES="User.Read,email,openid,profile"

# === Debug Settings ===
export DEBUG="true"                                     # Enable debug mode

Environment File Support: You can also create a `.env` file in your project directory with these variables for development convenience.

Python Client Library

Features

🔗 OData Client: Full CRUD operations on D365 F&O data entities with composite key support
📊 Metadata Management V2: Enhanced caching system with intelligent synchronization and FTS5 search
🏷️ Label Operations V2: Multilingual label caching with performance improvements and async support
🔍 Advanced Querying: Support for all OData query parameters ($select, $filter, $expand, etc.)
⚡ Action Execution: Execute bound and unbound OData actions with comprehensive parameter handling
�️ JSON Services: Generic access to D365 F&O JSON service endpoints (/api/services pattern)
�🔒 Authentication: Azure AD integration with default credentials, service principal, and Azure Key Vault support
💾 Intelligent Caching: Cross-environment cache sharing with module-based version detection
🌐 Async/Await: Modern async/await patterns with optimized session management
📝 Type Hints: Full type annotation support with enhanced data models
🤖 MCP Server: Production-ready Model Context Protocol server with 49 tools and 4 resource types
🖥️ Comprehensive CLI: Hierarchical command-line interface for all D365 F&O operations
🧪 Multi-tier Testing: Mock, sandbox, and live integration testing framework (17/17 tests passing)
📋 Metadata Scripts: PowerShell and Python utilities for entity, enumeration, and action discovery
🔐 Enhanced Credential Management: Support for Azure Key Vault and multiple credential sources
📊 Advanced Sync Management: Session-based synchronization with detailed progress tracking
🔧 NEW v0.3.0: Pydantic settings model with type-safe environment variable validation
📂 NEW v0.3.0: Custom log file path support and flexible logging configuration
🔄 NEW v0.3.0: Automatic legacy configuration migration and compatibility layer

Installation

bash

# Install from PyPI
pip install d365fo-client

# Or install from source
git clone https://github.com/mafzaal/d365fo-client.git
cd d365fo-client
uv sync  # Installs with exact dependencies from uv.lock

# Or use Docker (no local installation required)
docker pull ghcr.io/mafzaal/d365fo-client:latest

# Run with Docker
docker run --rm -it \
  -e D365FO_BASE_URL="https://your-environment.dynamics.com" \
  -e D365FO_CLIENT_ID="your-client-id" \
  -e D365FO_CLIENT_SECRET="your-client-secret" \
  -e D365FO_TENANT_ID="your-tenant-id" \
  -v d365fo-mcp:/home/mcp_user/ \
  ghcr.io/mafzaal/d365fo-client:latest

Note: The package includes MCP (Model Context Protocol) dependencies by default, enabling AI assistant integration. Both `d365fo-client` CLI and `d365fo-fastmcp-server` commands will be available after installation.

Breaking Change in v0.2.3: Environment variable names have been updated for consistency:

`AZURE_CLIENT_ID` → `D365FO_CLIENT_ID`
`AZURE_CLIENT_SECRET` → `D365FO_CLIENT_SECRET`
`AZURE_TENANT_ID` → `D365FO_TENANT_ID`

Please update your environment variables accordingly when upgrading.

Python Client Quick Start

Command Line Interface (CLI)

d365fo-client provides a comprehensive CLI with hierarchical commands for interacting with Dynamics 365 Finance & Operations APIs and metadata. The CLI supports all major operations including entity management, metadata discovery, and system administration.

Usage

bash

# Use the installed CLI command
d365fo-client [GLOBAL_OPTIONS] COMMAND [SUBCOMMAND] [OPTIONS]

# Alternative: Module execution
python -m d365fo_client.main [OPTIONS] COMMAND [ARGS]

Command Categories

Entity Operations

bash

# List entities with filtering
d365fo-client entities list --pattern "customer" --limit 10

# Get entity details and schema
d365fo-client entities get CustomersV3 --properties --keys --labels

# CRUD operations
d365fo-client entities create Customers --data '{"CustomerAccount":"US-999","Name":"Test"}'
d365fo-client entities update Customers US-999 --data '{"Name":"Updated Name"}'
d365fo-client entities delete Customers US-999

Metadata Operations

bash

# Search and discover entities
d365fo-client metadata entities --search "sales" --output json

# Get available actions
d365fo-client metadata actions --pattern "calculate" --limit 5

# Enumerate system enumerations
d365fo-client metadata enums --search "status" --output table

# Synchronize metadata cache
d365fo-client metadata sync --force-refresh

Version Information

bash

# Get application versions
d365fo-client version app
d365fo-client version platform  
d365fo-client version build

Label Operations

bash

# Resolve single label
d365fo-client labels resolve "@SYS13342"

# Search labels by pattern
d365fo-client labels search "customer" --language "en-US"

JSON Service Operations

bash

# Call SQL diagnostic services  
d365fo-client service sql-diagnostic GetAxSqlExecuting
d365fo-client service sql-diagnostic GetAxSqlResourceStats --since-minutes 5
d365fo-client service sql-diagnostic GetAxSqlBlocking --output json

# Generic JSON service calls
d365fo-client service call SysSqlDiagnosticService SysSqlDiagnosticServiceOperations GetAxSqlExecuting
d365fo-client service call YourServiceGroup YourServiceName YourOperation --parameters '{"param1":"value1"}'

Global Options

`--base-url URL` — Specify D365 F&O environment URL
`--profile NAME` — Use named configuration profile
`--output FORMAT` — Output format: json, table, csv, yaml (default: table)
`--verbose` — Enable verbose output for debugging
`--timeout SECONDS` — Request timeout (default: 30)

Configuration Profiles

Create reusable configurations in `~/.d365fo-client/config.yaml`:

yaml

profiles:
  production:
    base_url: "https://prod.dynamics.com"
    use_default_credentials: true
    timeout: 60
    
  development:
    base_url: "https://dev.dynamics.com" 
    client_id: "${D365FO_CLIENT_ID}"
    client_secret: "${D365FO_CLIENT_SECRET}"
    tenant_id: "${D365FO_TENANT_ID}"
    use_cache_first: true

default_profile: "development"

Examples

bash

# Quick entity discovery
d365fo-client entities list --pattern "cust.*" --output json

# Get comprehensive entity information
d365fo-client entities get CustomersV3 --properties --keys --labels --output yaml

# Search for calculation actions
d365fo-client metadata actions --pattern "calculate|compute" --output table

# Test environment connectivity
d365fo-client version app --verbose

For a complete command reference:

bash

d365fo-client --help
d365fo-client entities --help
d365fo-client metadata --help

Basic Usage

python

import asyncio
from d365fo_client import D365FOClient, FOClientConfig

async def main():
    # Simple configuration with default credentials
    config = FOClientConfig(
        base_url="https://your-fo-environment.dynamics.com",
        use_default_credentials=True  # Uses Azure Default Credential
    )
    
    async with D365FOClient(config) as client:
        # Test connection
        if await client.test_connection():
            print("✅ Connected successfully!")
        
        # Get environment information
        env_info = await client.get_environment_info()
        print(f"Environment: {env_info.application_version}")
        
        # Search for entities (uses metadata cache v2)
        customer_entities = await client.search_entities("customer")
        print(f"Found {len(customer_entities)} customer entities")
        
        # Get customers with query options
        from d365fo_client import QueryOptions
        options = QueryOptions(
            select=["CustomerAccount", "Name", "SalesCurrencyCode"],
            top=10,
            orderby=["Name"]
        )
        
        customers = await client.get_data("/data/CustomersV3", options)
        print(f"Retrieved {len(customers['value'])} customers")

if __name__ == "__main__":
    asyncio.run(main())

Using Convenience Function

python

from d365fo_client import create_client

# Quick client creation with enhanced defaults
async with create_client("https://your-fo-environment.dynamics.com") as client:
    customers = await client.get_data("/data/CustomersV3", top=5)

Configuration

Environment Variable Management (New in v0.3.0)

The d365fo-client now includes a comprehensive Pydantic settings model for type-safe environment variable management:

python

from d365fo_client import D365FOSettings, get_settings

# Get type-safe settings instance
settings = get_settings()

# Access settings with full IntelliSense support
print(f"Base URL: {settings.base_url}")
print(f"Log Level: {settings.log_level}")
print(f"Cache Directory: {settings.cache_dir}")

# Check configuration state
if settings.has_client_credentials():
    print("Client credentials configured")

startup_mode = settings.get_startup_mode()  # "profile_only", "default_auth", "client_credentials"

# Convert to environment dictionary for external tools
env_vars = settings.to_env_dict()

Key Benefits:

Type Safety: Automatic validation and type conversion for all 35+ environment variables
IDE Support: Full IntelliSense and autocompletion for configuration options
Environment Files: Support for `.env` files in development
Comprehensive Defaults: Sensible defaults for all configuration options
Validation: Built-in validation for URLs, ports, timeouts, and other settings

Authentication Options

python

from d365fo_client import FOClientConfig

# Option 1: Default Azure credentials (recommended)
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com",
    use_default_credentials=True
)

# Option 2: Client credentials
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com",
    client_id="your-client-id",
    client_secret="your-client-secret", 
    tenant_id="your-tenant-id",
    use_default_credentials=False
)

# Option 3: Azure Key Vault integration (New in v0.2.3)
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com",
    credential_source="keyvault",  # Use Azure Key Vault for credentials
    keyvault_url="https://your-keyvault.vault.azure.net/"
)

# Option 4: With custom settings
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com",
    use_default_credentials=True,
    verify_ssl=False,  # For development environments
    timeout=60,  # Request timeout in seconds
    metadata_cache_dir="./my_cache",  # Custom cache directory
    use_label_cache=True,  # Enable label caching
    label_cache_expiry_minutes=120  # Cache for 2 hours
)

Legacy Configuration Migration (New in v0.3.0)

The d365fo-client automatically detects and migrates legacy configuration files:

Automatic Detection: Identifies legacy configuration patterns (missing `verify_ssl`, outdated field names)
Field Migration: Updates `cache_dir` → `metadata_cache_dir`, `auth_mode` → `use_default_credentials`
Backup Creation: Creates backup of original configuration before migration
Seamless Upgrade: Ensures smooth transition from older versions without manual intervention

python

# Legacy configurations are automatically migrated when FastMCP server starts
# No manual intervention required - migration happens transparently

Core Operations

CRUD Operations

python

async with D365FOClient(config) as client:
    # CREATE - Create new customer (supports composite keys)
    new_customer = {
        "CustomerAccount": "US-999",
        "Name": "Test Customer",
        "SalesCurrencyCode": "USD"
    }
    created = await client.create_data("/data/CustomersV3", new_customer)
    
    # READ - Get single customer by key
    customer = await client.get_data("/data/CustomersV3('US-001')")
    
    # UPDATE - Update customer with optimistic concurrency
    updates = {"Name": "Updated Customer Name"}
    updated = await client.update_data("/data/CustomersV3('US-001')", updates)
    
    # DELETE - Delete customer
    success = await client.delete_data("/data/CustomersV3('US-999')")
    print(f"Delete successful: {success}")

Advanced Querying

python

from d365fo_client import QueryOptions

# Complex query with multiple options
options = QueryOptions(
    select=["CustomerAccount", "Name", "SalesCurrencyCode", "CustomerGroupId"],
    filter="SalesCurrencyCode eq 'USD' and contains(Name, 'Corp')",
    expand=["CustomerGroup"],
    orderby=["Name desc", "CustomerAccount"],
    top=50,
    skip=10,
    count=True
)

result = await client.get_data("/data/CustomersV3", options)
print(f"Total count: {result.get('@odata.count')}")

Action Execution

python

# Unbound action
result = await client.post_data("/data/calculateTax", {
    "amount": 1000.00,
    "taxGroup": "STANDARD"
})

# Bound action on entity set
result = await client.post_data("/data/CustomersV3/calculateBalances", {
    "asOfDate": "2024-12-31"
})

# Bound action on specific entity instance  
result = await client.post_data("/data/CustomersV3('US-001')/calculateBalance", {
    "asOfDate": "2024-12-31"
})

JSON Service Operations

python

# Basic JSON service call (no parameters)
response = await client.post_json_service(
    service_group="SysSqlDiagnosticService",
    service_name="SysSqlDiagnosticServiceOperations",
    operation_name="GetAxSqlExecuting"
)

if response.success:
    print(f"Found {len(response.data)} executing SQL statements")
    print(f"Status: HTTP {response.status_code}")
else:
    print(f"Error: {response.error_message}")

# JSON service call with parameters
from datetime import datetime, timezone, timedelta

end_time = datetime.now(timezone.utc)
start_time = end_time - timedelta(minutes=10)

response = await client.post_json_service(
    service_group="SysSqlDiagnosticService",
    service_name="SysSqlDiagnosticServiceOperations",
    operation_name="GetAxSqlResourceStats",
    parameters={
        "start": start_time.isoformat(),
        "end": end_time.isoformat()
    }
)

# Using JsonServiceRequest object for better structure
from d365fo_client.models import JsonServiceRequest

request = JsonServiceRequest(
    service_group="SysSqlDiagnosticService",
    service_name="SysSqlDiagnosticServiceOperations",
    operation_name="GetAxSqlBlocking"
)

response = await client.call_json_service(request)
print(f"Service endpoint: {request.get_endpoint_path()}")

# Multiple SQL diagnostic operations
operations = ["GetAxSqlExecuting", "GetAxSqlBlocking", "GetAxSqlLockInfo"]
for operation in operations:
    response = await client.post_json_service(
        service_group="SysSqlDiagnosticService",
        service_name="SysSqlDiagnosticServiceOperations",
        operation_name=operation
    )
    
    if response.success:
        count = len(response.data) if isinstance(response.data, list) else 1
        print(f"{operation}: {count} records")

# Custom service call template
response = await client.post_json_service(
    service_group="YourServiceGroup",
    service_name="YourServiceName",
    operation_name="YourOperation",
    parameters={
        "parameter1": "value1",
        "parameter2": 123,
        "parameter3": True
    }
)

Metadata Operations

python

# Intelligent metadata synchronization (v2 system)
sync_manager = await client.get_sync_manager()
await sync_manager.smart_sync()

# Search entities with enhanced filtering
sales_entities = await client.search_entities("sales")
print("Sales-related entities:", [e.name for e in sales_entities])

# Get detailed entity information with labels
entity_info = await client.get_public_entity_info("CustomersV3")
if entity_info:
    print(f"Entity: {entity_info.name}")
    print(f"Label: {entity_info.label_text}")
    print(f"Data Service Enabled: {entity_info.data_service_enabled}")

# Search actions with caching
calc_actions = await client.search_actions("calculate")
print("Calculation actions:", [a.name for a in calc_actions])

# Get enumeration information
enum_info = await client.get_public_enumeration_info("NoYes")
if enum_info:
    print(f"Enum: {enum_info.name}")
    for member in enum_info.members:
        print(f"  {member.name} = {member.value}")

Label Operations

python

# Get specific label (v2 caching system)
label_text = await client.get_label_text("@SYS13342")
print(f"Label text: {label_text}")

# Get multiple labels efficiently
labels = await client.get_labels_batch([
    "@SYS13342", "@SYS9490", "@GLS63332"
])
for label_id, text in labels.items():
    print(f"{label_id}: {text}")

# Enhanced entity info with resolved labels
entity_info = await client.get_public_entity_info_with_labels("CustomersV3")
if entity_info.label_text:
    print(f"Entity display name: {entity_info.label_text}")

# Access enhanced properties with labels
for prop in entity_info.enhanced_properties[:5]:
    if hasattr(prop, 'label_text') and prop.label_text:
        print(f"{prop.name}: {prop.label_text}")

Error Handling

python

from d365fo_client import D365FOClientError, AuthenticationError, ConnectionError

try:
    async with D365FOClient(config) as client:
        customer = await client.get_data("/data/CustomersV3('NON-EXISTENT')")
except ConnectionError as e:
    print(f"Connection failed: {e}")
except AuthenticationError as e:
    print(f"Authentication failed: {e}")
except D365FOClientError as e:
    print(f"Client operation failed: {e}")
    print(f"Status code: {e.status_code}")
    print(f"Response: {e.response_text}")

Development

Setting up Development Environment

bash

# Clone the repository
git clone https://github.com/mafzaal/d365fo-client.git
cd d365fo-client

# Install with development dependencies using uv
uv sync --dev

# Run tests
uv run pytest

# Run integration tests
.\tests\integration\integration-test-simple.ps1 test-sandbox

# Format code
uv run black .
uv run isort .

# Type checking
uv run mypy src/

# Quality checks
.\make.ps1 quality-check  # Windows PowerShell
# or
make quality-check       # Unix/Linux/macOS

Project Structure

code

d365fo-client/
├── src/
│   └── d365fo_client/
│       ├── __init__.py          # Public API exports
│       ├── main.py              # CLI entry point  
│       ├── cli.py               # CLI command handlers
│       ├── client.py            # Enhanced D365FOClient class
│       ├── config.py            # Configuration management
│       ├── auth.py              # Authentication management
│       ├── session.py           # HTTP session management
│       ├── crud.py              # CRUD operations
│       ├── query.py             # OData query utilities
│       ├── metadata.py          # Legacy metadata operations
│       ├── metadata_api.py      # Metadata API client
│       ├── metadata_cache.py    # Metadata caching layer V2
│       ├── metadata_sync.py     # Metadata synchronization V2 with session management
│       ├── sync_session.py      # Enhanced sync session management (New in v0.2.3)
│       ├── credential_manager.py # Credential source management (New in v0.2.3)
│       ├── labels.py            # Label operations V2
│       ├── profiles.py          # Profile data models
│       ├── profile_manager.py   # Profile management
│       ├── models.py            # Data models and configurations
│       ├── output.py            # Output formatting
│       ├── utils.py             # Utility functions
│       ├── exceptions.py        # Custom exceptions
│       └── mcp/                 # Model Context Protocol server
│           ├── __init__.py      # MCP server exports
│           ├── main.py          # MCP server entry point
│           ├── server.py        # Core MCP server implementation
│           ├── client_manager.py# D365FO client connection pooling
│           ├── models.py        # MCP-specific data models
│           ├── mixins/          # FastMCP tool mixins (49 tools)
│           ├── tools/           # Legacy MCP tools (deprecated)
│           │   ├── connection_tools.py
│           │   ├── crud_tools.py
│           │   ├── metadata_tools.py
│           │   └── label_tools.py
│           ├── resources/       # MCP resource handlers (4 types)
│           │   ├── entity_handler.py
│           │   ├── metadata_handler.py
│           │   ├── environment_handler.py
│           │   └── query_handler.py
│           └── prompts/         # MCP prompt templates
├── tests/                       # Comprehensive test suite
│   ├── unit/                    # Unit tests (pytest-based)
│   ├── integration/             # Multi-tier integration testing
│   │   ├── mock_server/         # Mock D365 F&O API server
│   │   ├── test_mock_server.py  # Mock server tests
│   │   ├── test_sandbox.py      # Sandbox environment tests ✅
│   │   ├── test_live.py         # Live environment tests
│   │   ├── conftest.py          # Shared pytest fixtures
│   │   ├── test_runner.py       # Python test execution engine
│   │   └── integration-test-simple.ps1 # PowerShell automation
│   └── test_mcp_server.py       # MCP server unit tests ✅
├── scripts/                     # Metadata discovery scripts
│   ├── search_data_entities.ps1 # PowerShell entity search
│   ├── get_data_entity_schema.ps1 # PowerShell schema retrieval
│   ├── search_enums.py          # Python enumeration search
│   ├── get_enumeration_info.py  # Python enumeration info
│   ├── search_actions.ps1       # PowerShell action search
│   └── get_action_info.py       # Python action information
├── docs/                        # Comprehensive documentation
├── pyproject.toml               # Project configuration
└── README.md                    # This file

Configuration Options

Option	Type	Default	Description
`base_url`	str	Required	D365 F&O base URL
`client_id`	str	None	Azure AD client ID
`client_secret`	str	None	Azure AD client secret
`tenant_id`	str	None	Azure AD tenant ID
`use_default_credentials`	bool	True	Use Azure Default Credential
`credential_source`	str	"environment"	Credential source: "environment", "keyvault"
`keyvault_url`	str	None	Azure Key Vault URL for credential storage
`verify_ssl`	bool	False	Verify SSL certificates
`timeout`	int	30	Request timeout in seconds
`metadata_cache_dir`	str	Platform-specific user cache	Metadata cache directory
`use_label_cache`	bool	True	Enable label caching V2
`label_cache_expiry_minutes`	int	60	Label cache expiry time
`use_cache_first`	bool	False	Enable cache-first mode with background sync

Cache Directory Behavior

By default, the client uses platform-appropriate user cache directories:

Windows: `%LOCALAPPDATA%\d365fo-client` (e.g., `C:\Users\username\AppData\Local\d365fo-client`)
macOS: `~/Library/Caches/d365fo-client` (e.g., `/Users/username/Library/Caches/d365fo-client`)
Linux: `~/.cache/d365fo-client` (e.g., `/home/username/.cache/d365fo-client`)

You can override this by explicitly setting `metadata_cache_dir`:

python

from d365fo_client import FOClientConfig

# Use custom cache directory
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com",
    metadata_cache_dir="/custom/cache/path"
)

# Or get the default cache directory programmatically
from d365fo_client import get_user_cache_dir

cache_dir = get_user_cache_dir("my-app")  # Platform-appropriate cache dir
config = FOClientConfig(
    base_url="https://your-fo-environment.dynamics.com", 
    metadata_cache_dir=str(cache_dir)
)

Testing

This project includes comprehensive testing at multiple levels to ensure reliability and quality.

Unit Tests

Run standard unit tests for core functionality:

bash

# Run all unit tests
uv run pytest

# Run with coverage
uv run pytest --cov=d365fo_client --cov-report=html

# Run specific test file
uv run pytest tests/test_client.py -v

Integration Tests

The project includes a sophisticated multi-tier integration testing framework:

Quick Start

bash

# Run sandbox integration tests (recommended)
.\tests\integration\integration-test-simple.ps1 test-sandbox

# Run mock server tests (no external dependencies)
.\tests\integration\integration-test-simple.ps1 test-mock

# Run with verbose output
.\tests\integration\integration-test-simple.ps1 test-sandbox -VerboseOutput

Test Levels

1. Mock Server Tests - Fast, isolated tests against a simulated D365 F&O API

2. Sandbox Tests ⭐ *(Default)* - Tests against real D365 F&O test environments

3. Live Tests - Optional tests against production environments

Configuration

Set up integration testing with environment variables:

bash

# Copy the template and configure
cp tests/integration/.env.template tests/integration/.env

# Edit .env file with your settings:
INTEGRATION_TEST_LEVEL=sandbox
D365FO_SANDBOX_BASE_URL=https://your-test.dynamics.com
D365FO_CLIENT_ID=your-client-id
D365FO_CLIENT_SECRET=your-client-secret
D365FO_TENANT_ID=your-tenant-id

Available Commands

bash

# Test environment setup
.\tests\integration\integration-test-simple.ps1 setup

# Dependency checking
.\tests\integration\integration-test-simple.ps1 deps-check

# Run specific test levels
.\tests\integration\integration-test-simple.ps1 test-mock
.\tests\integration\integration-test-simple.ps1 test-sandbox
.\tests\integration\integration-test-simple.ps1 test-live

# Coverage and reporting
.\tests\integration\integration-test-simple.ps1 coverage

# Clean up test artifacts
.\tests\integration\integration-test-simple.ps1 clean

Test Coverage

Integration tests cover:

✅ Connection & Authentication - Azure AD integration, SSL/TLS validation
✅ Version Methods - Application, platform, and build version retrieval
✅ Metadata Operations - Entity discovery, metadata API validation
✅ Data Operations - CRUD operations, OData query validation
✅ Error Handling - Network failures, authentication errors, invalid requests
✅ Performance - Response time validation, concurrent operations

For detailed information, see Integration Testing Documentation.

Test Results

Recent sandbox integration test results:

code

✅ 17 passed, 0 failed, 2 warnings in 37.67s
====================================================== 
✅ TestSandboxConnection::test_connection_success
✅ TestSandboxConnection::test_metadata_connection_success  
✅ TestSandboxVersionMethods::test_get_application_version
✅ TestSandboxVersionMethods::test_get_platform_build_version
✅ TestSandboxVersionMethods::test_get_application_build_version
✅ TestSandboxVersionMethods::test_version_consistency
✅ TestSandboxMetadataOperations::test_download_metadata
✅ TestSandboxMetadataOperations::test_search_entities
✅ TestSandboxMetadataOperations::test_get_data_entities
✅ TestSandboxMetadataOperations::test_get_public_entities
✅ TestSandboxDataOperations::test_get_available_entities
✅ TestSandboxDataOperations::test_odata_query_options
✅ TestSandboxAuthentication::test_authenticated_requests
✅ TestSandboxErrorHandling::test_invalid_entity_error
✅ TestSandboxErrorHandling::test_invalid_action_error
✅ TestSandboxPerformance::test_response_times
✅ TestSandboxPerformance::test_concurrent_operations

Contributing

1. Fork the repository

2. Create a feature branch (`git checkout -b feature/amazing-feature`)

3. Make your changes

4. Run tests (`uv run pytest`)

5. Run integration tests (`.\tests\integration\integration-test-simple.ps1 test-sandbox`)

6. Format code (`uv run black . && uv run isort .`)

7. Commit changes (`git commit -m 'Add amazing feature'`)

8. Push to branch (`git push origin feature/amazing-feature`)

9. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Changelog

See CHANGELOG.md for a list of changes and version history.

Support

📧 Email: mo@thedataguy.pro
🐛 Issues: GitHub Issues

Microsoft Dynamics 365
OData
Azure Identity
Model Context Protocol (MCP) - For AI assistant integration

Frequently asked questions

What is d365fo-client?

d365fo-client is A comprehensive Python client library and MCP server for Microsoft Dynamics 365 Finance & Operations (D365 F&O) that provides easy access to OData endpoints, metadata operations, label management, and AI assistant integration.

How do I install d365fo-client?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is d365fo-client open source?

Yes — it is hosted on GitHub at https://github.com/mafzaal/d365fo-client and has 13 stars.

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