MCP_Atom_of_Thoughts

Atom of Thoughts (AoT) is an MCP server that implements a decomposition-based reasoning framework. It structures problem-solving as a network of atoms categorized as premises, reasoning steps, hypotheses, verifications, and final conclusions. This setup enables explicit confidence tracking and verification across multiple thought paths, improving reliability for complex tasks. The AoT toolset includes two main variants: AoT (the full-featured version) and AoT-light (a faster, streamlined version with a reduced depth and simplified verification). Use AoT-light when you need rapid brainstorming or quick, high-level exploration; switch to AoT for deeper, more rigorous analysis that benefits from extended decomposition, verification, and multi-perspective consideration. The server exposes a workflow where you create premises, derive reasoning, formulate hypotheses, verify them, and eventually derive high-confidence conclusions, with an optional decomposition-contraction mechanism to explore sub-atoms and re-integrate results.

Prerequisites:\n- Node.js (v14+ recommended) and npm installed on your system.\n- Basic familiarity with running Node.js applications.\n\nStep-by-step installation:\n1) Clone the repository or download the AoT MCP server package.\n2) Navigate to the project directory.\n3) Install dependencies:\n npm install\n4) Start the server:\n npm run start or node server.js\n5) If the project uses a specific entry script or environment configuration, follow the repository’s README for additional setup (e.g., environment variables, config files).\n6) Verify the server is running by visiting the provided endpoint or checking the console/output for a listening port.\n\nNotes:\n- If a Dockerfile is provided, you can alternatively run the container with Docker using the image name specified in the repository.\n- For development, you may use a hot-reload setup if documented in the repo.

Tips and common considerations:\n- Review the five atom types (premise, reasoning, hypothesis, verification, conclusion) to structure your inputs effectively.\n- When using AoT-light, expect faster responses with shallower decomposition and a simplified verification path; use AoT for more rigorous verification and deeper analysis.\n- Enable verbose logging during troubleshooting to trace the decomposition and contraction processes.\n- If you encounter environment variable issues, ensure necessary variables (e.g., API keys, model endpoints, or storage paths) are defined in a .env file or the server startup command.\n- If the server exposes REST or WebSocket endpoints, consult the API section of the README for the exact routes and payload formats.\n- Monitor max-depth settings and termination criteria to balance speed versus thoroughness depending on your use case.