MCP Tools that may or may not be useful to others.
Documentation
MCP Toolz
mcp-name: io.github.taylorleese/mcp-toolz
MCP server for Claude Code that provides multi-LLM feedback tools.
Features
- Multi-LLM Feedback: Get second opinions from ChatGPT (OpenAI), Gemini (Google), and DeepSeek
- MCP Integration: Works with Claude Code via the Model Context Protocol
Quick Start
Installation
From PyPI (Recommended)
pip install mcp-toolzFrom Source (Development)
# Clone the repository
git clone https://github.com/taylorleese/mcp-toolz.git
cd mcp-toolz
# Create and activate virtual environment
python3 -m venv venv
source venv/bin/activate # macOS/Linux
# or: venv\Scripts\activate # Windows
# Install in editable mode with dev dependencies
pip install -e ".[dev]"Configuration
# Set your API keys as environment variables (at least one required for AI feedback tools)
export OPENAI_API_KEY=sk-... # For ChatGPT
export GOOGLE_API_KEY=... # For Gemini
export DEEPSEEK_API_KEY=sk-... # For DeepSeek
# Or create a .env file (if installing from source)
cp .env.example .env
# Edit .env and add your API keysMCP Server Setup
Add to your Claude Code MCP settings:
If installed via pip:
{
"mcpServers": {
"mcp-toolz": {
"command": "mcp-toolz",
"args": [],
"env": {
"OPENAI_API_KEY": "sk-...",
"GOOGLE_API_KEY": "...",
"DEEPSEEK_API_KEY": "sk-..."
}
}
}
}If installed from source:
{
"mcpServers": {
"mcp-toolz": {
"command": "python",
"args": ["-m", "mcp_server"],
"cwd": "/absolute/path/to/mcp-toolz",
"env": {
"PYTHONPATH": "/absolute/path/to/mcp-toolz/src"
}
}
}
}Restart Claude Code to load the MCP server.
MCP Server Tools
AI Feedback Tools
Get second opinions from multiple LLMs on code, architecture decisions, and implementation plans:
ask_chatgpt- Get ChatGPT's analysis (supports custom questions)ask_gemini- Get Gemini's analysis (supports custom questions)ask_deepseek- Get DeepSeek's analysis (supports custom questions)
Claude Code plugins
This repo doubles as a Claude Code plugin marketplace. Install all four with:
/plugin marketplace add taylorleese/mcp-toolz
/plugin install mcp-toolz-server@mcp-toolz
/plugin install precommit-detect@mcp-toolz
/plugin install revise-all-docs@mcp-toolz
/plugin install resolve-github-alerts@mcp-toolzmcp-toolz-server
Installs the mcp-toolz MCP server in Claude Code without manual editing of ~/.claude.json. Once installed, the three tools (ask_chatgpt, ask_gemini,
ask_deepseek) are available to the model in any Claude Code session. The plugin runs the server via uvx --from mcp-toolz python -m mcp_server, so PyPI
is still the underlying distribution channel — this is purely an installation-ergonomics layer for Claude Code users.
Required env vars (set in your shell or via direnv/.envrc): OPENAI_API_KEY, GOOGLE_API_KEY, DEEPSEEK_API_KEY. Each is independently optional — the
corresponding tool just returns an error if its key is unset.
For Cursor / Zed / Claude Desktop users: keep configuring the MCP server manually via your client's standard mechanism. Claude Code plugins don't propagate
to other clients.
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).
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@anthropicsresolve-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.
/resolve-github-alertsUsage Examples
Get Multiple AI Perspectives
I'm deciding between Redis and Memcached for caching user sessions.
Ask ChatGPT for their analysis.Follow up with:
- "Ask Gemini for another perspective"
- "What does DeepSeek think about this?"
Debug with Multiple Perspectives
I'm getting "TypeError: Cannot read property 'map' of undefined" in my React component.
The error occurs in UserList.jsx when rendering the users array.
Ask ChatGPT and Gemini for debugging suggestions.Environment Variables
# Required (at least one for AI feedback tools)
OPENAI_API_KEY=sk-... # Your OpenAI API key
GOOGLE_API_KEY=... # Your Google API key (for Gemini)
DEEPSEEK_API_KEY=sk-... # Your DeepSeek API key
# Optional
MCP_TOOLZ_MODEL=gpt-5 # OpenAI model (default: gpt-5)
MCP_TOOLZ_GEMINI_MODEL=gemini-2.0-flash-thinking-exp-01-21 # Gemini model
MCP_TOOLZ_DEEPSEEK_MODEL=deepseek-chat # DeepSeek modelTroubleshooting
"Error 401: Invalid API key"
- Verify API keys are set in
.envor environment variables - Check billing is enabled on your API provider account
"No module named context_manager"
- Use
PYTHONPATH=srcbefore running Python directly - Or install via pip:
pip install mcp-toolz
Project Structure
mcp-toolz/
├── src/
│ ├── mcp_server/ # MCP server for Claude Code
│ │ └── server.py # MCP tools and handlers
│ └── context_manager/ # Client implementations
│ ├── openai_client.py # ChatGPT API client
│ ├── gemini_client.py # Gemini API client
│ └── deepseek_client.py # DeepSeek API client
├── tests/ # pytest tests
├── requirements.in
└── requirements.txtDevelopment
Setup for Contributors
# Clone and install
git clone https://github.com/taylorleese/mcp-toolz.git
cd mcp-toolz
python3 -m venv venv
source venv/bin/activate
pip install -r requirements-dev.txt
# Install pre-commit hooks (IMPORTANT!)
pre-commit install
# Copy and configure .env
cp .env.example .env
# Edit .env with your API keysRunning Tests
source venv/bin/activate
pytestCode Quality
# Run all checks (runs automatically on commit after pre-commit install)
pre-commit run --all-files
# Individual tools
black .
ruff check .
mypy src/License
MIT
Similar MCP
Based on tags & features
Trending MCP
Most active this week