Sequential Thinking MCP Server
A Model Context Protocol (MCP) server that facilitates structured, progressive thinking through defined stages. This tool helps break down complex problems into sequential thoughts, track the progression of your thinking process, and generate summaries.
Features
- Structured Thinking Framework: Organizes thoughts through standard cognitive stages (Problem Definition, Research, Analysis, Synthesis, Conclusion)
- Thought Tracking: Records and manages sequential thoughts with metadata
- Related Thought Analysis: Identifies connections between similar thoughts
- Progress Monitoring: Tracks your position in the overall thinking sequence
- Summary Generation: Creates concise overviews of the entire thought process
- Persistent Storage: Automatically saves your thinking sessions
- Data Import/Export: Share and reuse thinking sessions
- Extensible Architecture: Easily customize and extend functionality
Prerequisites
- Python 3.10 or higher
- UV package manager (Install Guide)
Project Structure
mcp-sequential-thinking/
├── mcp_sequential_thinking/
│ ├── server.py # Main server implementation
│ ├── models.py # Data models
│ ├── storage.py # Persistence layer
│ ├── analysis.py # Thought analysis
│ └── __init__.py
├── tests/ # Unit tests
├── README.md
├── example.md # Customization examples
└── pyproject.toml
Quick Start
Set Up Project
# Create and activate virtual environment uv venv .venvScriptsactivate # Windows source .venv/bin/activate # Unix # Install package and dependencies uv pip install -e . # For development with testing tools uv pip install -e ".[dev]" # For all optional dependencies uv pip install -e ".[all]"
Run the Server
# Run directly uv run -m mcp_sequential_thinking.server # Or use the installed script mcp-sequential-thinking
Run Tests
# Run all tests pytest # Run with coverage report pytest --cov=mcp_sequential_thinking
Claude Desktop Integration
Add to your Claude Desktop configuration (%APPDATA%Claudeclaude_desktop_config.json
on Windows):
{
"mcpServers": {
"sequential-thinking": {
"command": "uv",
"args": [
"--directory",
"C:\path\to\your\mcp-sequential-thinking\run_server.py",
"run",
"server.py"
]
}
}
}
Alternatively, if you’ve installed the package with pip install -e .
, you can use:
{
"mcpServers": {
"sequential-thinking": {
"command": "mcp-sequential-thinking"
}
}
}
How It Works
The server maintains a history of thoughts and processes them through a structured workflow. Each thought is validated, categorized, and stored with relevant metadata for later analysis.
Usage Guide
The Sequential Thinking server exposes three main tools:
1. process_thought
Records and analyzes a new thought in your sequential thinking process.
Parameters:
thought
(string): The content of your thoughtthought_number
(integer): Position in your sequence (e.g., 1 for first thought)total_thoughts
(integer): Expected total thoughts in the sequencenext_thought_needed
(boolean): Whether more thoughts are needed after this onestage
(string): The thinking stage - must be one of:- “Problem Definition”
- “Research”
- “Analysis”
- “Synthesis”
- “Conclusion”
tags
(list of strings, optional): Keywords or categories for your thoughtaxioms_used
(list of strings, optional): Principles or axioms applied in your thoughtassumptions_challenged
(list of strings, optional): Assumptions your thought questions or challenges
Example:
# First thought in a 5-thought sequence
process_thought(
thought="The problem of climate change requires analysis of multiple factors including emissions, policy, and technology adoption.",
thought_number=1,
total_thoughts=5,
next_thought_needed=True,
stage="Problem Definition",
tags=["climate", "global policy", "systems thinking"],
axioms_used=["Complex problems require multifaceted solutions"],
assumptions_challenged=["Technology alone can solve climate change"]
)
2. generate_summary
Generates a summary of your entire thinking process.
Example output:
{
"summary": {
"totalThoughts": 5,
"stages": {
"Problem Definition": 1,
"Research": 1,
"Analysis": 1,
"Synthesis": 1,
"Conclusion": 1
},
"timeline": [
{"number": 1, "stage": "Problem Definition"},
{"number": 2, "stage": "Research"},
{"number": 3, "stage": "Analysis"},
{"number": 4, "stage": "Synthesis"},
{"number": 5, "stage": "Conclusion"}
]
}
}
3. clear_history
Resets the thinking process by clearing all recorded thoughts.
Practical Applications
- Decision Making: Work through important decisions methodically
- Problem Solving: Break complex problems into manageable components
- Research Planning: Structure your research approach with clear stages
- Writing Organization: Develop ideas progressively before writing
- Project Analysis: Evaluate projects through defined analytical stages
Getting Started
With the proper MCP setup, simply use the process_thought
tool to begin working through your thoughts in sequence. As you progress, you can get an overview with generate_summary
and reset when needed with clear_history
.
Customizing the Sequential Thinking Server
For detailed examples of how to customize and extend the Sequential Thinking server, see example.md. It includes code samples for:
- Modifying thinking stages
- Enhancing thought data structures
- Adding persistence
- Implementing enhanced analysis
- Creating custom prompts
- Setting up advanced configurations
License
MIT License
Sequential Thinking
Project Details
- arben-adm/mcp-sequential-thinking
- MIT License
- Last Updated: 4/20/2025
Recomended MCP Servers
MCP Server for Adobe After Effects. Enables remote control (compositions, text, shapes, solids, properties) via the Model Context...
Zotero MCP: Connects your Zotero research library with Claude and other AI assistants via the Model Context Protocol...
Sample MCP Server for Dify AI
A Model Context Protocol server for Ashra
The OpenAPI-MCP proxy translates OpenAPI specs into MCP tools, enabling AI agents to access external APIs without custom...
A comprehensive stdio MCP server for DataForSEO API
A TypeScript-based MCP server that enables testing of REST APIs through Cline. This tool allows you to test...
Model Context Protocol (MCP) server for Excalidraw - Work in Progress
An MCP (Model Context Protocol) server that provides Ethereum blockchain data tools via Etherscan's API. Features include checking...