Think

A minimal MCP Server based on the Anthropic's "think" tool research
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4 months ago

First Indexed

3 weeks ago

Catalog Refreshed

Documentation & install

Readme and setup notes from the catalogue, plus a client-ready config you can copy for your MCP host.

Installation

Add the following to your MCP client configuration file.

Configuration

View docs
{
  "mcpServers": {
    "marcopesani-think-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "think-mcp-server"
      ]
    }
  }
}

You get a minimal MCP server that lets Claude-like AI assistants use the dedicated think tool to pause and reflect during complex reasoning. This server runs as a local process and communicates over stdio, enabling structured tool usage during multi-step tasks while keeping your environment secure and predictable.

How to use

Configure your MCP client to point to the think server and start issuing prompts that explicitly request a think step when you need deeper analysis. The think tool logs Claude’s internal thoughts to a dedicated log without changing your data sources. Use it for complex, multi-step reasoning, policy-heavy guidance, or when outputs depend on analyzing prior tool results.

How to install

Prerequisites you need before installation: node and npm are installed on your system.

Install the server dependencies and build locally.

npm install
npm run build
npm run watch

Configuration and usage notes

The think server is designed to run as a local stdio MCP endpoint. You configure clients to connect via standard input/output streams and reference the think tool to allow the AI to pause and reason in a structured way. The server exposes a single tool named think with a required field thought that represents Claude’s thinking process.

Getting started with clients

To connect Claude Desktop or other MCP clients to the think server, use the following runtime command configuration.

{
  "mcpServers": {
    "think": {
      "command": "npx",
      "args": ["-y", "think-mcp-server"]
    }
  }
}

Troubleshooting and debugging

Debugging MCP endpoints can be challenging because communication happens over stdio. If you need more visibility, use an inspector tool to monitor the MCP traffic and internal logs.

Available tools

think

A tool that lets the AI pause during response generation to reflect on its reasoning. It logs the thought process without altering external data sources and helps with complex, multi-step tasks.

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