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Sequential Thinking MCP Server (Python Implementation)

MIT License

A Python implementation of the Sequential Thinking MCP server using the official Model Context Protocol (MCP) Python SDK. This server facilitates a detailed, step-by-step thinking process for problem-solving and analysis.

Features

  • Break down complex problems into manageable steps
  • Revise and refine thoughts as understanding deepens
  • Branch into alternative paths of reasoning
  • Adjust the total number of thoughts dynamically
  • Generate and verify solution hypotheses

Usage

Running Directly

uv --directory "/path/to/sequential-thinking-mcp" run main.py

Development Mode

For development and testing, you can use the MCP CLI tools:

# Install MCP CLI tools pip install "mcp[cli]" # Run in development mode mcp dev "/path/to/sequential-thinking-mcp" # npx @modelcontextprotocol/inspector npx @modelcontextprotocol/inspector uv --diectory "/path/to/sequential-thinking-mcp" run main.py

Integration

mcp install "\path\to\sequential-thinking-mcp\server.py"
{ "mcpServers": { "sequential-thinking": { "command": "uv", "args": [ "--directory", "/path/to/sequential-thinking-mcp", "run", "main.py" ] } } }

Sequential Thinking Tool

The server provides a tool called sequential_thinking with the following parameters:

  • thought (string): The current thinking step
  • thoughtNumber (integer): Current thought number
  • totalThoughts (integer): Estimated total thoughts needed
  • nextThoughtNeeded (boolean): Whether another thought step is needed
  • isRevision (boolean, optional): Whether this revises previous thinking
  • revisesThought (integer, optional): Which thought is being reconsidered
  • branchFromThought (integer, optional): Branching point thought number
  • branchId (string, optional): Branch identifier
  • needsMoreThoughts (boolean, optional): If more thoughts are needed

Resources

The server provides the following resources for accessing thought data:

  • thoughts://history: Get the complete thought history
  • thoughts://branches/{branch_id}: Get thoughts for a specific branch
  • thoughts://summary: Get a summary of all thoughts and branches

Prompts

  • thinking_process_guide: Guide for using the sequential thinking process

Example Usage

# First thought sequential_thinking( thought="First, we need to understand the problem requirements.", thoughtNumber=1, totalThoughts=5, nextThoughtNeeded=True ) # Second thought sequential_thinking( thought="Now, let's analyze the key constraints.", thoughtNumber=2, totalThoughts=5, nextThoughtNeeded=True ) # Revise a thought sequential_thinking( thought="Actually, we need to clarify the problem requirements first.", thoughtNumber=1, totalThoughts=5, nextThoughtNeeded=True, isRevision=True, revisesThought=1 ) # Branch from thought 2 sequential_thinking( thought="Let's explore an alternative approach.", thoughtNumber=3, totalThoughts=5, nextThoughtNeeded=True, branchFromThought=2, branchId="alternative-approach" )

Integration with Claude or Other AI Assistants

To use this server with Claude or other AI assistants that support MCP:

  1. Install the MCP server in Claude Desktop using the MCP CLI
  2. The AI can then use the sequential_thinking tool to break down complex problems

About Model Context Protocol (MCP)

The Model Context Protocol (MCP) is a standardized way for applications to provide context and tools to LLMs. It allows:

  • Resources: Providing contextual data to the LLM
  • Tools: Exposing functionality for the LLM to take actions
  • Prompts: Defining reusable templates for LLM interactions

For more information, visit modelcontextprotocol.io

License

MIT License. See LICENSE for details.

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