Chain of Thought MCP Server
by beverm2391
This MCP Server leverages Groq's API to access LLMs, specifically Qwen's qwq model, to expose raw chain-of-thought tokens. It enhances AI performance by enabling a 'think' tool for complex tasks.
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What is Chain of Thought MCP Server?
This is a Chain of Thought MCP (Model Control Program) server that utilizes Groq's API to access LLMs and expose raw chain-of-thought tokens from Qwen's qwq model. It allows AI agents to use a 'think' tool to improve performance on complex tasks.
How to use Chain of Thought MCP Server?
- Clone the repository. 2. Run
uv syncto install dependencies. 3. Obtain a Groq API key. 4. Update your MCP configuration with the provided JSON snippet, replacing the path and API key with your local values. 5. Instruct your AI agent to call thechain_of_thoughttool on every request, providing guidelines for its usage as a scratchpad.
Key features of Chain of Thought MCP Server
Exposes raw chain-of-thought tokens
Uses Groq's API for fast inference
Integrates with Qwen's qwq model
Enhances AI agent reasoning
Provides a 'think' tool for complex tasks
Use cases of Chain of Thought MCP Server
Improving performance on SWE Bench
Enabling AI agents to reason through complex problems
Verifying user requests and data
Planning actions and ensuring compliance with policies
Iterating over tool results for correctness
FAQ from Chain of Thought MCP Server
What is an MCP server?
What is an MCP server?
An MCP server provides a way to control and interact with models.
Why use chain of thought?
Why use chain of thought?
Chain of thought allows the model to reason step-by-step, leading to better results.
What is Groq?
What is Groq?
Groq provides fast inference for LLMs.
What is Qwen's qwq model?
What is Qwen's qwq model?
Qwen's qwq model is a large language model.
How does this improve AI performance?
How does this improve AI performance?
By allowing the AI to 'think' through the problem before responding, it can generate more accurate and reliable results.