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python-sequential-thinking-mcp

MCP.Pizza Chef: XD3an

The python-sequential-thinking-mcp is a Python-based MCP server that implements the Sequential Thinking protocol using the official MCP Python SDK. It enables models to break down complex problems into manageable steps, revise and refine thoughts dynamically, explore alternative reasoning paths, and generate and verify solution hypotheses, facilitating detailed and structured multi-step reasoning workflows.

Use This MCP server To

Break down complex problems into sequential reasoning steps Dynamically adjust reasoning depth during problem analysis Explore alternative solution paths with branching thoughts Generate and verify hypotheses in multi-step workflows Refine and revise thoughts as new information emerges

README

Sequential Thinking MCP Server (Python Implementation)

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

python-sequential-thinking-mcp FAQ

How do I run the python-sequential-thinking-mcp server directly?
Use the command `uv --directory "/path/to/sequential-thinking-mcp" run main.py` to start the server.
Can I develop and test this MCP server locally?
Yes, install the MCP CLI tools with `pip install "mcp[cli]"` and run `mcp dev "/path/to/sequential-thinking-mcp"` for development mode.
What Python SDK does this MCP server use?
It uses the official Model Context Protocol (MCP) Python SDK for implementation.
Does this server support dynamic adjustment of reasoning steps?
Yes, it allows dynamically changing the total number of thoughts during the reasoning process.
Can this MCP server handle branching in reasoning?
Yes, it supports branching into alternative paths of reasoning for complex problem-solving.
Is this MCP server suitable for hypothesis generation and verification?
Yes, it facilitates generating and verifying solution hypotheses as part of the sequential thinking process.
What are the main benefits of using this MCP server?
It structures complex problem-solving into manageable, revisable, and verifiable steps, improving clarity and accuracy.
Can this MCP server integrate with other LLM providers?
Yes, it is provider-agnostic and can work with OpenAI, Claude, Gemini, and other LLMs.