mcp-toolz
MCP Tools that may or may not be useful to others.
Documentation
Claude Toolz
A Claude Code plugin marketplace: four plugins for second opinions, security triage, docs upkeep, and pre-commit setup.
Nothing here needs to be installed from a package index. The plugins are markdown, shell, and one standard-library Python script.
Install
/plugin marketplace add taylorleese/claude-toolz
/plugin install ask-llm@claude-toolz
/plugin install precommit-detect@claude-toolz
/plugin install resolve-github-alerts@claude-toolz
/plugin install revise-all-docs@claude-toolzInstall only the ones you want — they are independent.
Plugins
`ask-llm`
Gets a second opinion from a non-Claude frontier model: Codex (OpenAI's coding agent), Antigravity (Google's coding agent), or DeepSeek.
Two ways in. Ask in plain language — "ask Codex what it thinks of this schema", "get a second opinion on this plan", "what would another model say about
this bug" — and Claude invokes the skill. Or drive it explicitly:
/ask-llm codex is this migration reversible?
/ask-llm all which caching strategy would you pick here?
/ask-llm does this error handling miss anything?The first word selects the provider when it is `codex`, `agy`, `deepseek`, or `all`; otherwise the whole argument is the question and it defaults to
Codex. `all` runs all three concurrently — OpenAI, Google, and DeepSeek — and summarizes where they agree and disagree.
Providers come in two flavors. CLI providers drive a locally installed agent that authenticates with your own subscription, so there is no API key to
manage at all. HTTP providers call a REST endpoint and need a key exported in the shell profile Claude Code inherits (`~/.zshrc`, `~/.bashrc`).
| Provider | Transport | Auth | Default model | Model override |
|---|---|---|---|---|
| `codex` | CLI | `codex login` — no API key | CLI default | `ASK_LLM_CODEX_MODEL` |
| `agy` | CLI | authenticated on first run — no API key | CLI default | `ASK_LLM_AGY_MODEL` |
| `deepseek` | HTTP | `DEEPSEEK_API_KEY` | `deepseek-chat` | `ASK_LLM_DEEPSEEK_MODEL` |
`codex` is the best default: no key to manage, a coding agent rather than a raw chat model, and it runs in a read-only sandbox so it cannot touch your
working tree. `agy` is its Google counterpart and the best partner for a cross-vendor check.
Measured on a trivial prompt, the split is roughly:
| Provider | Latency |
|---|---|
| `deepseek` | ~1.4s |
| `codex` | ~5.5s |
| `agy` | ~6.4s |
The CLI agents reason before answering; that is the cost of depth and of needing no API key. Reach for `deepseek` when you want an answer immediately.
One constraint on `agy`: it ignores stdin, so context rides in the command-line argument and is capped at 256 KB. Larger contexts are refused with a clear
error and should go to `codex`, which reads stdin and has no such limit.
Checking readiness
`/ask-llm status` prints what is actually usable on this machine — no model call, so it costs nothing:
PROVIDER TRANSPORT STATE DETAIL
deepseek http ready DEEPSEEK_API_KEY is set
codex cli ready Logged in using ChatGPT
agy cli unknown installed; no status command, auth verified only when calledWhen a CLI provider's session has lapsed it reports `unauthenticated` along with the exact command to run. Logins are interactive, so the script never
tries to drive one itself — it names the command and Claude relays it.
Turning a provider off
Set `ASK_LLM_DISABLED_PROVIDERS` to a comma-separated list to hide providers you cannot use, so they are never picked and never surface an error:
export ASK_LLM_DISABLED_PROVIDERS=deepseekThe script uses only the Python standard library — nothing to install and no dependency to keep patched.
`precommit-detect`
Read-only check for pre-commit setup state. Registers `SessionStart` and `PostToolUse:EnterWorktree` hooks that detect whether the current repo's
`.pre-commit-config.yaml` is wired up — pre-commit binary present, `.git/hooks/pre-commit` installed, Docker daemon reachable when the config requires it.
When something is missing, the hook surfaces the gap as `additionalContext` so Claude can walk you through approval-gated installs (one prompt per missing
item — never auto-installs).
`resolve-github-alerts`
Triages and resolves GitHub security alerts (Dependabot, code scanning, secret scanning) across **pip / pip-tools / poetry / uv / npm / yarn / pnpm / cargo /
go-modules / Docker / GitHub Actions** ecosystems. Run it in any repo to:
- Fix failing Dependabot PRs (lint/test issues)
- Bump vulnerable dependencies and recompile lockfiles
- Remediate code scanning and secret scanning alerts
- Submit a single PR with all fixes for manual review
Auto-detects the project's verify commands (Makefile targets, pre-commit, ruff, pytest, npm scripts) — no per-project configuration required.
Two ways in, same as `ask-llm`. Run it explicitly, optionally narrowing the scope:
/resolve-github-alerts
/resolve-github-alerts dependabot onlyOr just ask — "fix the security alerts on this repo", "clean up the failing Dependabot PRs" — and Claude invokes the skill. Because it creates a branch and
opens a pull request, the skill is written to trigger only on a clear request to remediate, not when you are merely asking what the alerts are.
`revise-all-docs`
Two ways to keep CLAUDE.md, README.md, and `docs//*.md`** in sync — pick by intent.
`/revise-all-docs` — *"I just finished some work. Capture what we learned."*
Reads the current conversation, pulls out commands discovered, gotchas hit, and patterns enforced, and proposes additions to the right doc file for each
finding (project-internal context → `CLAUDE.md`, user-facing onboarding → `README.md`, deeper how-to → `docs/`). Run this at the end of a session that
uncovered something worth recording.
`/improve-all-docs` — *"Forget the session. Audit the docs as they stand today."*
Statically scans every doc file, scores each against type-appropriate rubrics (install steps actually work? public command/API surface complete? versions and
paths current? intra-doc links resolve? duplicated content?), then proposes targeted fixes — including deletions of stale or duplicated content, not just
additions. Run this during cleanup passes, before a release, or when docs feel out of sync with the code.
The `all-docs-improver` skill is the same audit auto-invoked when you ask in plain language ("are my docs up to date?", "check the README and docs"). The
slash command is explicit; the skill is hands-free.
Required dependency
Both surfaces delegate `CLAUDE.md` work to the official `claude-md-management` plugin:
/plugin install claude-md-management@anthropicsDevelopment
git clone https://github.com/taylorleese/claude-toolz.git
cd claude-toolz
make install-dev| Command | What it does |
|---|---|
| `make test` | Run the test suite |
| `make lint` | Run all linters via pre-commit |
| `make format` | Auto-format |
| `make check-plugins` | Verify every plugin in `marketplace.json` resolves on disk |
| `make refresh-plugins` | Refresh the local marketplace mirror and installed plugins |
| `make all` | format + lint + test |
Releasing a plugin change
There is no package to publish. Bump `version` in the plugin's `.claude-plugin/plugin.json`, merge to `main`, then run `make refresh-plugins`. Claude Code
keys its install cache by version, so skipping the bump makes the update a silent no-op.
Repository layout
claude-toolz/
├── .claude-plugin/
│ └── marketplace.json # the four plugins advertised to Claude Code
├── plugins/
│ ├── ask-llm/
│ ├── precommit-detect/
│ ├── resolve-github-alerts/
│ └── revise-all-docs/
├── scripts/
│ └── check_plugins.py # marketplace manifest validator
└── tests/License
MIT
Frequently asked questions
What is mcp-toolz?
mcp-toolz is MCP Tools that may or may not be useful to others.
How do I install mcp-toolz?
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 mcp-toolz open source?
Yes — it is hosted on GitHub at https://github.com/taylorleese/mcp-toolz and has 2 stars.
Related MCP tools
AWS MCP Servers — helping you get the most out of AWS, wherever you use MCP. Python-based implementation. Trusted by 6900+ developers.
A simple, secure MCP-to-OpenAPI proxy server Python-based implementation. Trusted by 3500+ developers. Trusted by 3500+ developers.
MCP server that interacts with Obsidian via the Obsidian rest API community plugin Python-based implementation. Trusted by 2300+ developers.
Default Configuration: MCP CLI defaults to using Ollama with the gpt-oss reasoning model for local, privacy-focused operation without requiring API keys.
Official MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
MCP server for long term agent memory with Mem0. Also useful as a template to get you started building your own MCP server with Python!
Run your own MCP server? See who uses it and what to fix.
Measure it with TrackMCP