consult7
MCP server to consult a language model with large context size Python-based implementation.
Documentation
Consult7 MCP Server
Consult7 is a Model Context Protocol (MCP) server that enables AI agents to consult large context window models via OpenRouter for analyzing extensive file collections - entire codebases, document repositories, or mixed content that exceed the current agent's context limits.
Why Consult7?
Consult7 enables any MCP-compatible agent to offload file analysis to large context models (up to 2M tokens). Useful when:
- Agent's current context is full
- Task requires specialized model capabilities
- Need to analyze large codebases in a single query
- Want to compare results from different models
> "For Claude Code users, Consult7 is a game changer."
How it works
Consult7 collects files from the specific paths you provide (with optional wildcards in filenames), assembles them into a single context, and sends them to a large context window model along with your query. The result is directly fed back to the agent you are working with.
Example Use Cases
Quick codebase summary
- Files: `["/Users/john/project/src/*.py", "/Users/john/project/lib/*.py"]`
- Query: "Summarize the architecture and main components of this Python project"
- Model: `"google/gemini-3-flash-preview"`
- Mode: `"fast"`
Deep analysis with reasoning
- Files: `["/Users/john/webapp/src/*.py", "/Users/john/webapp/auth/*.py", "/Users/john/webapp/api/*.js"]`
- Query: "Analyze the authentication flow across this codebase. Think step by step about security vulnerabilities and suggest improvements"
- Model: `"anthropic/claude-opus-4.8"`
- Mode: `"think"`
Generate a report saved to file
- Files: `["/Users/john/project/src/*.py", "/Users/john/project/tests/*.py"]`
- Query: "Generate a comprehensive code review report with architecture analysis, code quality assessment, and improvement recommendations"
- Model: `"google/gemini-2.5-pro"`
- Mode: `"think"`
- Output File: `"/Users/john/reports/code_review.md"`
- Result: Returns `"Result has been saved to /Users/john/reports/code_review.md"` instead of flooding the agent's context
Featured: Gemini 3.1 Models
Consult7 supports Google's Gemini 3.1 family:
- Gemini 3.1 Pro (`google/gemini-3.1-pro-preview`) - Flagship reasoning model, 1M context
- Gemini 3 Flash (`google/gemini-3-flash-preview`) - Ultra-fast model, 1M context
- Gemini 3.1 Flash Lite (`google/gemini-3.1-flash-lite-preview`) - Ultra-fast lite model, 1M context
Quick mnemonics for power users:
- `gemt` = Gemini 3.1 Pro + think (flagship reasoning)
- `gemf` = Gemini 3 Flash + fast (ultra fast)
- `gptt` = GPT-5.6 Sol + think (latest GPT)
- `grot` = Grok 4.20 + think (automatic reasoning)
- `oput` = Claude Opus 4.8 + think (adaptive thinking)
- `fabt` = Claude Fable 5 + think (deepest reasoning; premium — reserved for hard problems)
- `ULTRA` = Run GEMT, GPTT, GROT, and OPUT in parallel (4 frontier models)
- `FUSE` = Fusion: a frontier panel deliberates and a judge synthesizes, in one call
These mnemonics make it easy to reference model+mode combinations in your queries.
> Note on Fable 5. `anthropic/claude-fable-5` is Anthropic's most capable model but priced at a premium (~2× Opus 4.8). It does not replace Opus 4.8 as the default Claude workhorse and is not part of the `ULTRA` panel — reach for it deliberately, only on specifically hard problems where the extra depth is worth the cost. Unlike Opus 4.8 (adaptive thinking only), OpenRouter honors Fable's effort scale, so `mid`/`think` map to `effort=high`/`effort=xhigh`.
Featured: Fusion (multi-model analysis)
Consult7 supports OpenRouter's Fusion (`openrouter/fusion`) — a single call where a panel of frontier models (Opus, GPT, Gemini Pro) answers your query in parallel and a judge model synthesizes their responses into one answer. Reach for it on hard questions where multiple perspectives help and the cost of being wrong outweighs a few extra completions.
- Context: 128K — smaller than the 1M–2M single models, so it's best for hard questions on moderate input, not giant file bundles.
- Mode → research depth: `fast` / `mid` / `think` map the panel's web-search/fetch budget to `max_tool_calls` of 2 / 8 / 16.
- Mnemonic: `FUSE` = `openrouter/fusion`.
Trivial prompts answer directly (no panel); the panel fires only when the question warrants deliberation. Fusion is billed per panel run, so it costs more than a single-model call.
Installation
Claude Code
Simply run:
claude mcp add -s user consult7 uvx -- consult7 your-openrouter-api-keyClaude Desktop
Add to your Claude Desktop configuration file:
{
"mcpServers": {
"consult7": {
"type": "stdio",
"command": "uvx",
"args": ["consult7", "your-openrouter-api-key"]
}
}
}Replace `your-openrouter-api-key` with your actual OpenRouter API key.
No installation required - `uvx` automatically downloads and runs consult7 in an isolated environment.
Command Line Options
uvx consult7 [--test]- ``: Required. Your OpenRouter API key
- `--test`: Optional. Test the API connection
The model and mode are specified when calling the tool, not at startup.
Supported Models
Consult7 supports all 500+ models available on OpenRouter. Below are the flagship models with optimized dynamic file size limits:
| Model | Context | Use Case |
|---|---|---|
| `openai/gpt-5.6-sol` | 1M | Latest top-tier GPT, effort-based reasoning |
| `google/gemini-3.1-pro-preview` | 1M | Flagship reasoning model |
| `google/gemini-3-flash-preview` | 1M | Gemini 3 Flash, ultra fast |
| `google/gemini-3.1-flash-lite-preview` | 1M | Ultra-fast lite model |
| `anthropic/claude-fable-5` | 1M | Most capable; premium price — reserved for hard problems |
| `anthropic/claude-opus-4.8` | 1M | Best quality, adaptive thinking |
| `anthropic/claude-sonnet-4.6` | 1M | Excellent reasoning, fast |
| `anthropic/claude-haiku-4.5` | 200k | Budget, very fast |
| `x-ai/grok-4.20` | 2M | Automatic reasoning, huge context |
| `x-ai/grok-4.1-fast` | 2M | Largest context window |
| `openrouter/fusion` | 128k | Multi-model panel + judge (see Featured: Fusion) |
Quick mnemonics:
- `gptt` = `openai/gpt-5.6-sol` + `think` (latest GPT, deep reasoning)
- `gemt` = `google/gemini-3.1-pro-preview` + `think` (Gemini 3.1 Pro, flagship reasoning)
- `grot` = `x-ai/grok-4.20` + `think` (Grok 4.20, automatic reasoning)
- `oput` = `anthropic/claude-opus-4.8` + `think` (Claude Opus, adaptive thinking)
- `opuf` = `anthropic/claude-opus-4.8` + `fast` (Claude Opus, no reasoning)
- `fabt` = `anthropic/claude-fable-5` + `think` (Claude Fable, deepest reasoning [effort xhigh]; premium, hard problems only)
- `fabm` = `anthropic/claude-fable-5` + `mid` (Claude Fable, high-effort reasoning; premium)
- `gemf` = `google/gemini-3-flash-preview` + `fast` (Gemini 3 Flash, ultra fast)
- `ULTRA` = call GEMT, GPTT, GROT, and OPUT IN PARALLEL (4 frontier models for maximum insight; Fable is deliberately not in the panel)
- `FUSE` = `openrouter/fusion` (one call: a frontier panel deliberates, a judge synthesizes; mode sets web-research depth)
You can use any OpenRouter model ID (e.g., `deepseek/deepseek-r1-0528`). See the full model list. File size limits are automatically calculated based on each model's context window.
Performance Modes
- `fast`: No reasoning - quick answers, simple tasks
- `mid`: Moderate reasoning - code reviews, bug analysis
- `think`: Maximum reasoning - security audits, complex refactoring
File Specification Rules
- Absolute paths only: `/Users/john/project/src/*.py`
- Wildcards in filenames only: `/Users/john/project/*.py` (not in directory paths)
- Extension required with wildcards: `*.py` not `*`
- Mix files and patterns: `["/path/src/*.py", "/path/README.md", "/path/tests/*_test.py"]`
Common patterns:
- All Python files: `/path/to/dir/*.py`
- Test files: `/path/to/tests/*_test.py` or `/path/to/tests/test_*.py`
- Multiple extensions: `["/path/*.js", "/path/*.ts"]`
Automatically ignored: `__pycache__`, `.env`, `secrets.py`, `.DS_Store`, `.git`, `node_modules`
Size limits: Dynamic based on model context window (e.g., Grok 4.20: ~8MB, GPT-5.6 Sol: ~4MB)
Tool Parameters
The consultation tool accepts the following parameters:
- files (required): List of absolute file paths or patterns with wildcards in filenames only
- query (required): Your question or instruction for the LLM to process the files
- model (required): The LLM model to use (see Supported Models above)
- mode (required): Performance mode - `fast`, `mid`, or `think`
- output_file (optional): Absolute path to save the response to a file instead of returning it
- If the file exists, it will be saved with `_updated` suffix (e.g., `report.md` → `report_updated.md`)
- When specified, returns only: `"Result has been saved to /path/to/file"`
- Useful for generating reports, documentation, or analyses without flooding the agent's context
- zdr (optional): Enable Zero Data Retention routing (default: `false`)
- When `true`, routes only to endpoints with ZDR policy (prompts not retained by provider)
- ZDR available: Gemini 3.1 Pro/Flash, Claude Opus 4.8, GPT-5, GPT-5.5
- Not available: GPT-5.6 Sol, Grok 4.20, Claude Fable 5 (returns error)
Usage Examples
Via MCP in Claude Code
Claude Code will automatically use the tool with proper parameters:
{
"files": ["/Users/john/project/src/*.py"],
"query": "Explain the main architecture",
"model": "google/gemini-3-flash-preview",
"mode": "fast"
}Via Python API
from consult7.consultation import consultation_impl
result = await consultation_impl(
files=["/path/to/file.py"],
query="Explain this code",
model="google/gemini-3-flash-preview",
mode="fast", # fast, mid, or think
provider="openrouter",
api_key="sk-or-v1-..."
)Testing
# Test OpenRouter connection
uvx consult7 sk-or-v1-your-api-key --testUninstalling
To remove consult7 from Claude Code:
claude mcp remove consult7 -s userVersion History
v3.9.0
- New default GPT: GPT-5.6 Sol (`openai/gpt-5.6-sol`) — the latest top-tier GPT, ~1M context / 128K output, effort-based reasoning (`mid` → `effort=medium`, `think` → `effort=high`). Replaces GPT-5.5 as the `gptt` default; GPT-5.5 stays available as a legacy model. ZDR is not supported on GPT-5.6 Sol (GPT-5.5 still is).
- Grok 4.5 not added: `x-ai/grok-4.5` is region-restricted on OpenRouter (returns a 403 "not available in your region") and could not be verified against the real API, so it was not integrated. Grok 4.20 remains the `grot` default.
v3.8.0
- Added Claude Fable 5 (`anthropic/claude-fable-5`) — Anthropic's most capable model, 1M context. Premium price (~2× Opus 4.8), so it's reserved for specifically hard problems and is not part of the `ULTRA` panel; it does not replace Opus 4.8 as the default Claude model. New mnemonics `fabt` (think) / `fabm` (mid). Unlike Opus 4.8 (adaptive thinking only), OpenRouter honors Fable's effort scale, so `mid`/`think` map to `effort=high`/`effort=xhigh` (`max` intentionally not exposed — it tends to overthink at ~2× token cost). ZDR not supported (Fable requires 30-day retention).
- Response-length prompt tuned: the system prompt now asks the model to match answer length to the task (thorough when the question needs depth, concise otherwise) instead of a blunt "be concise".
v3.7.1
- Surface mid-stream API errors: when OpenRouter sends an error as a streaming data chunk (after the initial 200), the call now returns that error message instead of a misleading "No content received".
v3.7.0
- Added Fusion (`openrouter/fusion`) — a multi-model panel plus a judge in one call; `mode` maps to web-research depth (`fast`/`mid`/`think` → `max_tool_calls` 2/8/16). New `FUSE` mnemonic.
- Upgraded Claude Opus 4.7 → 4.8 (1M context, adaptive thinking); `oput`/`opuf` now point to 4.8, and 4.7 is kept as a legacy ID.
- The response footer now reports the call cost in USD (from OpenRouter usage accounting), e.g. `cost: $0.0923`.
v3.6.1
- Toggle-reasoning footer now distinguishes `mid` vs `think` for adaptive models (Opus, Grok)
- Friendlier error message when a model has no Zero Data Retention endpoint
- `output_file` return now includes the metadata footer so callers can verify what ran
v3.6.0
- Upgraded models: GPT-5.5, Claude Opus 4.7, Grok 4.20
- Claude Opus 4.7 (1M context) uses adaptive thinking — `reasoning.enabled=true`
- Grok 4.20 (2M context) uses automatic reasoning — `reasoning.enabled=true`
- Updated mnemonics: `gptt` → GPT-5.5, `oput`/`opuf` → Claude Opus 4.7, `grot` → Grok 4.20
- Legacy model IDs still supported
v3.5.0
- Upgraded GPT-5.2 → GPT-5.4 (~1M context)
v3.4.0
- Upgraded models: Gemini 3.1 Pro, Claude Opus 4.6, Claude Sonnet 4.6, Grok 4.1 Fast
- Added new models: Claude Haiku 4.5, Gemini 3.1 Flash Lite
- Updated mnemonics: `gemt` → Gemini 3.1 Pro, `oput`/`opuf` → Claude Opus 4.6
- Legacy model IDs still supported
v3.3.0
- Fixed GPT-5.2 thinking mode truncation issue (switched to streaming)
- Added `google/gemini-3-flash-preview` (Gemini 3 Flash, ultra fast)
- Updated `gemf` mnemonic to use Gemini 3 Flash
- Added `zdr` parameter for Zero Data Retention routing
v3.2.0
- Updated to GPT-5.2 with effort-based reasoning
v3.1.0
- Added `google/gemini-3-pro-preview` (1M context, flagship reasoning model)
- New mnemonics: `gemt` (Gemini 3 Pro), `grot` (Grok 4), `ULTRA` (parallel execution)
v3.0.0
- Removed Google and OpenAI direct providers - now OpenRouter only
- Removed `|thinking` suffix - use `mode` parameter instead (now required)
- Clean `mode` parameter API: `fast`, `mid`, `think`
- Simplified CLI from `consult7 ` to `consult7 `
- Better MCP integration with enum validation for modes
- Dynamic file size limits based on model context window
v2.1.0
- Added `output_file` parameter to save responses to files
v2.0.0
- New file list interface with simplified validation
- Reduced file size limits to realistic values
License
MIT
Frequently asked questions
What is consult7?
consult7 is MCP server to consult a language model with large context size Python-based implementation.
How do I install consult7?
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 consult7 open source?
Yes — it is hosted on GitHub at https://github.com/szeider/consult7 and has 254 stars.
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