Chain of Thought MCP Server
by beverm2391
This MCP Server leverages Groq's API to access LLMs and expose raw chain-of-thought tokens from Qwen's qwq model. It enhances AI performance by enabling a 'think' tool for complex tasks.
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What is Chain of Thought MCP Server?
The Chain of Thought MCP Server is a tool that allows AI agents to utilize a chain-of-thought process by calling Groq's API and accessing LLMs, specifically Qwen's qwq model, to generate raw chain-of-thought tokens. This enables the AI to 'think' through complex problems before responding.
How to use Chain of Thought MCP Server?
- Clone the repository. 2. Install dependencies using
uv sync. 3. Obtain a Groq API key. 4. Configure your MCP server settings with the provided JSON snippet, ensuring the path points to the server's location and the Groq API key is correctly set. 5. Instruct the AI agent to use thechain_of_thoughttool on every request by adding the provided XML rules to the agent's configuration.
Key features of Chain of Thought MCP Server
Exposes raw chain-of-thought tokens
Uses Groq's API for fast LLM inference
Based on Qwen's qwq model
Improves AI performance on complex tasks
Easy installation and configuration
Use cases of Chain of Thought MCP Server
Enhancing AI agent reasoning and problem-solving
Improving performance on tasks requiring complex tool use
Providing a 'scratchpad' for AI agents to plan and verify actions
Enabling AI agents to follow specific rules and policies
FAQ from Chain of Thought MCP Server
What is a Chain of Thought?
What is a Chain of Thought?
Chain of Thought is a method where the AI generates a series of intermediate reasoning steps before arriving at a final answer.
Why use Groq's API?
Why use Groq's API?
Groq's API provides fast inference for LLMs, making the chain-of-thought process more efficient.
What is the Qwen qwq model?
What is the Qwen qwq model?
Qwen's qwq model is a large language model known for its performance and ability to generate coherent text.
How does this improve AI performance?
How does this improve AI performance?
By providing a 'think' tool, the AI can break down complex problems into smaller steps, leading to more accurate and reliable results.
Can I use this with other LLMs?
Can I use this with other LLMs?
This server is specifically designed for use with Groq's API and Qwen's qwq model. Adapting it to other LLMs may require significant modifications.