Sequential Thinking MCP Server

A Model Context Protocol (MCP) server providing a structured thinking journal: schema-validated thoughts, an append-only audit trail, structural analysis, and session export/import. It records and organizes a thinking process through defined stages — it does not evaluate, generate, or improve the reasoning itself; that stays with whatever model is calling it.

Features

• Structured Thinking Framework: Organizes thoughts through standard cognitive stages (Problem Definition, Research, Analysis, Synthesis, Conclusion), with warnings (or, in --strict-stages mode, rejection) when a thought skips or backtracks a stage
• Revisions & Branching: Revise earlier thoughts or fork alternative lines of reasoning, with revision- and branch-aware analysis and summaries
• Thought Tracking: Records and manages sequential thoughts with metadata as a structured, typed audit trail (structured_content on every tool response)
• Related Thought Analysis: Finds thoughts that are lexically similar to the current one, independent of stage, plus a separate same-tag/same-stage grouping — a categorical signal, not a claim of semantic relevance
• Progress Monitoring: Explicit mainline position, total recorded thoughts, branch count, and revision count — not a single ambiguous percentage
• Summary Generation: Extracts the actual recorded thinking (per-stage excerpts, aggregated challenged assumptions, open branches, revision chains) alongside structural statistics — a deterministic extraction, not new reasoning
• Persistent Storage: Append-only JSONL session log with thread-safety and automatic crash recovery
• Data Import/Export: Share and reuse thinking sessions
• Extensible Architecture: Easily customize and extend functionality
• Robust Error Handling: Protocol/validation errors (bad stage, duplicate thought number, path traversal) fail the call outright; execution errors the caller can adapt to come back as a normal tool result
• Type Safety: Comprehensive type annotations (mypy --strict clean) and Pydantic validation, including declared output schemas for every tool

Prerequisites

• Python 3.10 or higher
• UV package manager (Install Guide)

Key Technologies

• Pydantic: For data validation, serialization, and structured tool output schemas
• Portalocker: For thread-safe file access
• MCP Python SDK 2.x (mcp.server.mcpserver.MCPServer): For Model Context Protocol integration

Project Structure

mcp-sequential-thinking/
├── mcp_sequential_thinking/
│   ├── server.py       # Main server implementation and MCP tools
│   ├── models.py       # Data models with Pydantic validation
│   ├── storage.py      # Thread-safe persistence layer
│   ├── storage_utils.py # Shared utilities for storage operations
│   ├── analysis.py     # Thought analysis and pattern detection
│   ├── utils.py        # Common utilities and helper functions
│   ├── logging_conf.py # Centralized logging configuration
│   └── __init__.py     # Package initialization
├── tests/              
│   ├── test_analysis.py # Tests for analysis functionality
│   ├── test_models.py   # Tests for data models
│   ├── test_storage.py  # Tests for persistence layer
│   └── __init__.py
├── run_server.py       # Server entry point script
├── debug_mcp_connection.py # Utility for debugging connections
├── README.md           # Main documentation
├── CHANGELOG.md        # Version history and changes
├── example.md          # Customization examples
├── LICENSE             # MIT License
└── pyproject.toml      # Project configuration and dependencies

Quick Start

The package is published on PyPI as mcp-sequential-thinking. The easiest way to run it is via uvx — no install step needed:

uvx mcp-sequential-thinking

Or install it permanently:

pip install mcp-sequential-thinking
mcp-sequential-thinking

Development Setup

To work on the code, clone the repository and set it up from source:

1. Set Up Project

   # Create and activate virtual environment
   uv venv
   .venv\Scripts\activate  # 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]"
   

2. Run the Server

   # Run directly
   uv run -m mcp_sequential_thinking.server
   
   # Or use the installed script
   mcp-sequential-thinking
   

3. Run Tests

   # Run all tests
   pytest
   
   # Run with coverage report
   pytest --cov=mcp_sequential_thinking
   

Claude Desktop Integration

Add to your Claude Desktop configuration:

• Linux: ~/.config/Claude/claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%\Claude\claude_desktop_config.json

Option 1: Using uvx with the PyPI package (recommended)

No clone, no venv, no manual updates — uvx fetches the package from PyPI and runs it:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": ["mcp-sequential-thinking"]
    }
  }
}

To test unreleased changes, point uvx at the repository instead:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/arben-adm/mcp-sequential-thinking",
        "mcp-sequential-thinking"
      ]
    }
  }
}

Option 2: Using the installed entry point

If you've installed the package with pip install mcp-sequential-thinking (or pip install -e . from a clone):

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "mcp-sequential-thinking"
    }
  }
}

Option 3: Using a local clone's virtual environment (development)

If you have set up the project with uv venv && uv pip install -e ., point directly to the venv Python interpreter. This avoids dependency resolution issues (e.g., on systems with Python 3.14+):

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "/path/to/mcp-sequential-thinking/.venv/bin/python",
      "args": [
        "-m",
        "mcp_sequential_thinking.server"
      ],
      "cwd": "/path/to/mcp-sequential-thinking"
    }
  }
}

Option 4: Using uv run on a local clone (development)

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/mcp-sequential-thinking",
        "-m",
        "mcp_sequential_thinking.server"
      ]
    }
  }
}

Editor & IDE Integration

Cursor

Add to your Cursor MCP configuration at .cursor/mcp.json in your project root (or globally at ~/.cursor/mcp.json):

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": ["mcp-sequential-thinking"]
    }
  }
}

VS Code (Copilot MCP)

VS Code supports MCP servers since version 1.99+. Add to .vscode/mcp.json in your workspace or to your user settings.json:

{
  "servers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": ["mcp-sequential-thinking"]
    }
  }
}

Note: Enable MCP support in VS Code via "chat.mcp.enabled": true in your settings.

Zed

Add to your Zed settings (~/.config/zed/settings.json):

{
  "context_servers": {
    "sequential-thinking": {
      "command": {
        "path": "uvx",
        "args": ["mcp-sequential-thinking"]
      }
    }
  }
}

Claude Code (CLI)

Add the server using the CLI:

claude mcp add sequential-thinking -- uvx mcp-sequential-thinking

Or manually create/edit .mcp.json in your project root:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": ["mcp-sequential-thinking"]
    }
  }
}

Windsurf

Add to your Windsurf MCP configuration at ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "uvx",
      "args": ["mcp-sequential-thinking"]
    }
  }
}

Gemini CLI

Add to your Gemini CLI settings at ~/.gemini/settings.json:

{
  "mcpServers": {
    "sequential-thinking": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-sequential-thinking"],
      "env": {}
    }
  }
}

Tip: All editor configurations above run the published PyPI package via uvx. To run from a local clone instead (e.g. for development), use uv run --directory /path/to/mcp-sequential-thinking -m mcp_sequential_thinking.server or point directly to the venv Python interpreter (see Claude Desktop Options 3 and 4).

How It Works

The server maintains a history of thoughts and processes them through a structured workflow. Each thought is validated using Pydantic models, categorized into thinking stages, and stored with relevant metadata in a thread-safe storage system. The server automatically handles data persistence, backup creation, and provides tools for analyzing relationships between thoughts.

Sessions are persisted as an append-only JSONL log at ~/.mcp_sequential_thinking/current_session.jsonl (override the directory with the MCP_STORAGE_DIR environment variable). Each process_thought call appends a single fsynced line, so the file doubles as an audit trail and a truncated final line from an interrupted write is recovered automatically. Sessions from v0.5.x (current_session.json) are migrated losslessly on first start; the original file is kept as current_session.json.migrated-to-v2.

Usage Guide

The Sequential Thinking server exposes five main tools:

1. process_thought

Records and analyzes a new thought in your sequential thinking process.

Parameters:

• thought (string): The content of your thought
• thought_number (integer): Position in your sequence (e.g., 1 for first thought)
• total_thoughts (integer): Expected total thoughts in the sequence
• next_thought_needed (boolean): Whether more thoughts are needed after this one
• stage (string): The thinking stage - must be one of:
  • "Problem Definition"
  • "Research"
  • "Analysis"
  • "Synthesis"
  • "Conclusion"
• tags (list of strings, optional): Keywords or categories for your thought
• axioms_used (list of strings, optional): Principles or axioms applied in your thought
• assumptions_challenged (list of strings, optional): Assumptions your thought questions or challenges
• is_revision (boolean, optional): Whether this thought revises an earlier one
• revises_thought_number (integer, optional): The number of the earlier thought being revised (required together with is_revision)
• branch_from_thought (integer, optional): The thought number to fork from when exploring an alternative path
• branch_id (string, optional): Identifier for the branch (letters, digits, -, _; max 64 characters; requires branch_from_thought)

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"],
)

# Revise an earlier thought
process_thought(
    thought="Framing the problem purely around emissions was too narrow; adaptation matters equally.",
    thought_number=6,
    total_thoughts=6,
    next_thought_needed=True,
    stage="Problem Definition",
    is_revision=True,
    revises_thought_number=1,
)

# Fork an alternative line of reasoning
process_thought(
    thought="What if we approach this from a market-incentive angle instead?",
    thought_number=7,
    total_thoughts=7,
    next_thought_needed=True,
    stage="Analysis",
    branch_from_thought=3,
    branch_id="market-incentives",
)

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"},
      {"number": 6, "stage": "Problem Definition", "isRevision": true},
      {"number": 7, "stage": "Analysis", "branchId": "market-incentives"}
    ],
    "branches": {
      "market-incentives": {"fromThought": 3, "thoughtCount": 1}
    },
    "revisionCount": 1
  }
}

3. clear_history

Resets the thinking process by clearing all recorded thoughts.

4. export_session

Exports the current thinking session to a JSON file for sharing or backup.

Parameters:

• file_path (string): Path to the output JSON file. Since v0.6.0, exports are confined to the exports/ subdirectory of the storage directory; relative paths resolve to ~/.mcp_sequential_thinking/exports/ and parent directories are created automatically.

Example:

export_session(file_path="my-analysis.json")
# -> written to ~/.mcp_sequential_thinking/exports/my-analysis.json

5. import_session

Imports a previously exported thinking session from a JSON file. Exports created with v0.5.x remain importable.

Parameters:

• file_path (string): Path to the JSON file to import. Like exports, resolved inside the exports/ subdirectory of the storage directory.

Comparison to the official sequential-thinking server

The official MCP sequential-thinking server provides the core paradigm: numbered thoughts with revisions and branching, held in memory for the duration of the process. This server implements the same paradigm and adds:

• Persistence: sessions survive restarts (append-only JSONL log with crash recovery and automatic migration), and can be exported, shared and re-imported as JSON.
• Thinking stages: thoughts are categorized into cognitive stages (Problem Definition, Research, Analysis, Synthesis, Conclusion), enabling stage-based filtering and completeness checks.
• Analysis: related-thought detection via stages and tags, per-thought progress, and rich summaries including branch and revision statistics.

If you only need ephemeral chain-of-thought scaffolding, the official server is a lighter choice; if you want durable, analyzable thinking sessions, this one is built for that.

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 with Pydantic
• Adding persistence with databases
• Implementing enhanced analysis with NLP
• Creating custom prompts
• Setting up advanced configurations
• Building web UI integrations
• Implementing visualization tools
• Connecting to external services
• Creating collaborative environments
• Separating test code
• Building reusable utilities

License

MIT License