
~10k+ downloads on PulseMCP and counting. Over 1k monthly tool calls via Smithery. Listed on 12+ orchestration platforms. Security rating 4.3 on MSEEP.ai.
Vibe Check acts as a supportive meta-mentor for AI coding agents. It interrupts tunnel vision, asks clarifying questions, improves workflow efficiency and records what worked so the next run is smarter. Think of it as an adaptive debugging partner that acts as a built-in oversight layer.
TL;DR: Vibe Check keeps agents on track through short reflective pauses, preventing agents getting stuck in loops of thinking (RLI) and improving overall workflow efficiency.
LLMs often follow the first solution they imagine. Once that pattern takes hold they elaborate on it even if it drifts from the original goal. Without an external nudge the agent seldom questions its direction, leading to misalignment, overengineering and wasted cycles.
- vibe_check – Adaptive meta-mentor step that questions plans and highlights unstated assumptions.
- vibe_learn – Optional log of mistakes and solutions to gradually improve over time.
- History continuity – Prior feedback is automatically provided for a sense of memory.
- Multi-LLM flexibility – Choose Gemini, OpenAI or OpenRouter by overriding two fields.
- Meta-mentor prompt rewritten for methodology-focused guidance.
- History continuity enabled by default for richer conversations.
- Multi-provider support (Gemini, OpenAI, OpenRouter) with simple overrides.
vibe_learn
made optional for privacy-conscious deployments.- Repository restructured with Vitest unit tests and CI workflow.
- Smithery tool listing fixed via lazy loading.
# Clone and install
git clone https://github.com/PV-Bhat/vibe-check-mcp-server.git
cd vibe-check-mcp-server
npm install
npm run build
This project targets Node 20+. If you see a TypeScript error about a
duplicate require
declaration when building with Node 20.19.3, ensure your
dependencies are up to date (npm install
) or use the Docker setup below which
handles the build automatically.
Create a .env
file with the API keys you plan to use:
# Gemini (default)
GEMINI_API_KEY=your_gemini_api_key
# Optional providers
OPENAI_API_KEY=your_openai_api_key
OPENROUTER_API_KEY=your_openrouter_api_key
# Optional overrides
DEFAULT_LLM_PROVIDER=gemini
DEFAULT_MODEL=gemini-2.5-pro
Start the server:
npm start
See docs/TESTING.md for instructions on how to run tests.
The repository includes a helper script for one-command setup. It builds the
image, saves your GEMINI_API_KEY
and configures the container to start
automatically whenever you log in:
bash scripts/docker-setup.sh
This script:
- Creates
~/vibe-check-mcp
for persistent data - Builds the Docker image and sets up
docker-compose.yml
- Prompts for your API key and writes
~/vibe-check-mcp/.env
- Installs a systemd service (Linux) or LaunchAgent (macOS) so the container starts at login
- Generates
vibe-check-tcp-wrapper.sh
which proxies Cursor IDE to the server
After running it, open Cursor IDE → Settings → MCP and add a new server of type Command pointing to:
~/vibe-check-mcp/vibe-check-tcp-wrapper.sh
See Automatic Docker Setup for full details.
If you prefer to run the commands manually:
docker build -t vibe-check-mcp .
docker run -e GEMINI_API_KEY=your_gemini_api_key -p 3000:3000 vibe-check-mcp
Add to claude_desktop_config.json
:
"vibe-check": {
"command": "node",
"args": ["/path/to/vibe-check-mcp/build/index.js"],
"env": { "GEMINI_API_KEY": "YOUR_GEMINI_API_KEY" }
}
In your agent's system prompt, make it clear that vibe_check
is a mandatory tool for reflection. Always pass the full user request and other relevant context. After correcting a mistake, you can optionally log it with vibe_learn
to build a history for future analysis.
Example snippet:
As an autonomous agent you will:
1. Call vibe_check after planning and before major actions.
2. Provide the full user request and your current plan.
3. Optionally, record resolved issues with vibe_learn.
Tool | Purpose |
---|---|
🛑 vibe_check | Challenge assumptions and prevent tunnel vision |
🔄 vibe_learn | Capture mistakes, preferences and successes |
- Agent Prompting Strategies
- Advanced Integration
- Technical Reference
- Automatic Docker Setup
- Philosophy
- Case Studies
- Changelog
- Additional examples for OpenRouter models
- Repomix access to pass repositories to VC
- Agents.md addendum to improve plug-and-play integration
Contributions are welcome! See CONTRIBUTING.md.
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