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PV-Bhat/vibe-check-mcp-server: The definitive Vibe Coder's sanity check MCP server: Prevent cascading errors in AI workflows by implementing strategic pattern interrupts. Uses tool call "Vibe Check" with LearnLM 2.0 Flash, fine-tuned for pedagogy and metacognition to enhance complex workflow strategy, and prevents tunnel vision errors.

Adaptive metacognitive oversight for autonomous AI agents – a research-backed MCP server keeping LLMs aligned, reflective and safe.

The Most Widely-Deployed Feedback Layer in the MCP Ecosystem

~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.

VibeCheck MCP is a lightweight server implementing Anthropic's Model Context Protocol. It acts as an AI meta-mentor for your agents, interrupting pattern inertia with Critical Path Interrupts (CPI) to prevent Reasoning Lock-In (RLI). Think of it as a rubber-duck debugger for LLMs – a quick sanity check before your agent goes down the wrong path.

The Problem: Pattern Inertia & Reasoning Lock-In

Large language models can confidently follow flawed plans. Without an external nudge they may spiral into overengineering or misalignment. VibeCheck provides that nudge through short reflective pauses, improving reliability and safety.

Feature Description Benefits CPI Adaptive Interrupts Phase-aware prompts that challenge assumptions alignment, robustness Multi-provider LLM Gemini, OpenAI and OpenRouter support flexibility History Continuity Summarizes prior advice when sessionId is supplied context retention Optional vibe_learn Log mistakes and fixes for future reflection self-improvement Quickstart & Installation 
# 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:

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:

~/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
Integrating with Claude Desktop

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" }
}
import { vibe_check } from 'vibe-check-mcp';
const result = await vibe_check({
  goal: 'Write unit tests',
  plan: 'Use vitest for coverage',
  sessionId: 'demo1'
});
console.log(result.questions);
flowchart TD
  A[Agent Phase] --> B{Monitor Progress}
  B -- high risk --> C[CPI Interrupt]
  C --> D[Reflect & Adjust]
  B -- smooth --> E[Continue]
Loading Adaptive Metacognitive Interrupts (CPI) Advanced CPI Details The CPI architecture monitors planning, implementation and review phases. When uncertainty spikes, VibeCheck pauses execution, poses clarifying questions and resumes once the agent acknowledges the feedback. Agent Prompting Essentials

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

See docs/philosophy.md for the alignment research behind VibeCheck. The approach draws inspiration from Reflexion, Constitutional AI and other high-trust frameworks.

This repository includes a CI-based security scan that runs on every pull request. It checks dependencies with npm audit and scans the source for risky patterns. See SECURITY.md for details and how to report issues.

  1. Benchmarks and latency profiling
  2. Adaptive tuning based on agent performance
  3. Multi-agent cooperation support
  4. Optional human-in-the-loop review

Contributions are welcome! See CONTRIBUTING.md and join our Discord for discussion.

VibeCheck MCP is released under the MIT License. Built for reliable, enterprise-ready AI agents.

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