広告掲載
MCP.so
ログイン

Thinking Partner MCP Server

@nwant

リポジトリ

基本情報

カテゴリ

その他

トランスポート

stdio

作者

nwant

Thinking Partner MCP Server について

MCP server for unified AI thinking partner across Claude Desktop and Code

Thinking Partner MCP Server の設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "thinking-partner": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-thinking-partner"
      ]
    }
  }
}

Thinking Partner MCP Server のツール

ツール一覧はまだありません

この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。

上のボタンで一時的なサンドボックスでこのサーバーを実行し、ツール一覧を取得できます。

概要

What is Thinking Partner MCP?

Thinking Partner MCP is a Model Context Protocol (MCP) server that creates a unified AI thinking partner across Claude Desktop and Claude Code. It enables seamless context sharing and conversation continuity between architectural thinking and implementation work.

How to use Thinking Partner MCP?

Install dependencies with npm install, then configure both Claude Desktop (npm run setup-desktop) and Claude Code (npm run setup-code). Start the development server with npm run dev. For multi-machine sync, set environment variables like THINKING_PARTNER_GIT_REMOTE in a .env file.

Key features of Thinking Partner MCP

  • set_focus: Set a shared work topic across both tools.
  • get_context: Retrieve relevant context for the current conversation.
  • log_design_decision: Capture architectural choices with reasoning.
  • log_implementation_finding: Record discoveries made during coding.
  • bridge_conversation: Connect conversations between Desktop and Code.
  • Automatic Git synchronization for context across multiple machines.

Use cases of Thinking Partner MCP

  • Morning design session in Claude Desktop to explore architecture and log decisions.
  • Implementation session in Claude Code that automatically pulls in design context.
  • Next-day continuity where both tools remember reasoning and open questions.
  • Cross-session pattern recognition through persistent context storage.

よくある質問

1

What tools does Thinking Partner MCP provide?

It offers five tools: `set_focus`, `get_context`, `log_design_decision`, `log_implementation_finding`, and `bridge_conversation`.

2

How does context persist between sessions?

Context is stored persistently in a local JSON file (`data/context.json`), which is automatically read and written by the server.

3

Does Thinking Partner MCP support syncing across multiple machines?

Yes, by setting environment variables in a `.env` file (e.g., `THINKING_PARTNER_GIT_REMOTE`), the server can automatically pull before reading and commit/push after saving changes.

4

What are the runtime requirements?

Node.js and npm are required. The server is configured for Claude Desktop and Claude Code via the provided setup scripts.

5

How do I configure Claude Desktop and Claude Code?

Run `npm run setup-desktop` for Claude Desktop and `npm run setup-code` for Claude Code. Both scripts automatically configure the MCP server.

コメント

「その他」の他のコンテンツ

YOUB

Connect your AI assistant to your own YOUB endurance training account. Read recorded activities with full analysis, planned sessions, race goals, wellness (HRV, sleep, resting HR) and your athletic profile. Create or mov

🚀 Model Context Protocol (MCP) Curriculum for Beginners

microsoft

This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable,

16.7K
N

Next Generation Movers: free moving quotes (remote MCP)

Next Generation Movers

Free moving quotes for AI agents from Next Generation Movers, a licensed interstate mover (USDOT 3764697). US long-distance nationwide and local DC/MD/VA. Indicative ballpark price and booking options; optional $0.01 x40

Handl

Handl speaks the Model Context Protocol. Your whole billing operation — projects, invoices, clients, reports, approvals — as tools any AI assistant can call, inside your autonomy rules.

DeepMark

DeepMark helps teachers deliver rapid, consistent marking with meaningful feedback for every student — in a fraction of the time. What once took a week, now takes one free period.

広告掲載