What does the “think” tool do?
It allows Claude to pause during response generation and add an explicit thinking step—with its own designated space—to reason about whether all necessary information is available before proceeding.
@MCP-Mirror
基本情報
Mirror of
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": {
"marcopesani_think-mcp-server": {
"command": "docker",
"args": [
"build",
"-t",
"think-mcp-server",
"."
]
}
}
}Enables Claude to think about a problem or analyze information
think-mcp-server is a minimal Model Context Protocol (MCP) server that provides Claude AI models with the "think" tool capability. Based on Anthropic’s research published on March 20, 2025, the "think" tool gives Claude a dedicated reasoning step during response generation to improve complex, multi‑step tool‑use tasks.
Install globally via npm install -g think-mcp-server or run with npx -y think-mcp-server. For Claude Desktop, add the server configuration to claude_desktop_config.json (MacOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%/Claude/). Similar configuration steps are provided for Cline, Cursor, and Docker. Once configured, include instructions in your prompts to tell Claude when and how to use the “think” tool.
think with a required thought string parameter.It allows Claude to pause during response generation and add an explicit thinking step—with its own designated space—to reason about whether all necessary information is available before proceeding.
You can install it globally via npm (`npm install -g think-mcp-server`) or run it on demand with `npx -y think-mcp-server`. Docker build and run instructions are also provided.
Add the following JSON to your `claude_desktop_config.json` file (located in `~/Library/Application Support/Claude/` on MacOS or `%APPDATA%/Claude/` on Windows): `{"mcpServers":{"think":{"command":"npx","args":["-y","think-mcp-server"]}}}`.
Anthropic’s evaluations showed a 54% relative improvement on the τ‑Bench airline domain (pass^1 metric: 0.570 vs 0.370 baseline) and a 1.6% average improvement on SWE‑bench, along with enhanced consistency across trials.
The server runs as a standalone process and communicates over stdio using the Model Context Protocol. No authentication or additional transport is mentioned.

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Model Context Protocol Servers
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