Structured Thinking MCP Server

Name: Structured Thinking MCP Server
Author: Promptly-Technologies-LLC

@Promptly-Technologies-LLC

关于 Structured Thinking MCP Server

A TypeScript Model Context Protocol (MCP) server to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection

#ai #mcp #mindmap #mcp-server

基本信息

分类

其他

许可证

MIT

运行时

node

传输方式

stdio

发布者

Promptly-Technologies-LLC

配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "structured-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "structured-thinking"
      ]
    }
  }
}

工具

未检测到工具

工具是从 README 中自动提取的。维护者可以在 ## Tools 标题下列出工具,即可填充这部分内容。

概览

What is Structured Thinking MCP Server?

A TypeScript Model Context Protocol (MCP) server that allows LLMs to programmatically construct mind maps for exploring an idea space, with enforced metacognitive self-reflection. It is based on Arben Ademi's Sequential Thinking Python server.

How to use Structured Thinking MCP Server?

Configure the tool in Claude Desktop, Cursor, or another MCP client using the JSON setting with "command": "npx" and "args": ["-y", "structured-thinking"]. The server exposes MCP tools such as capture_thought, revise_thought, retrieve_relevant_thoughts, get_thinking_summary, and clear_thinking_history.

Key features of Structured Thinking MCP Server

Thought quality scores (0–1) for metacognitive feedback
Thought stages (e.g., Problem Definition, Analysis) to steer thinking
Branching to explore parallel lines of reasoning
Short-term memory buffer (10 most recent thoughts)
Long-term memory retrieval based on tags
Summarization of entire thinking process

Use cases of Structured Thinking MCP Server

LLMs constructing structured mind maps during problem-solving
Enforcing self-reflection and metacognitive awareness in reasoning
Exploring multiple solution branches simultaneously
Debugging or reviewing an LLM's thought process step-by-step

FAQ from Structured Thinking MCP Server

How are thought quality scores used?

Each thought is assigned a quality score between 0 and 1, which combines with the thought's stage to provide metacognitive feedback that steers the LLM's thinking process.

What are thought stages and why are they important?

Each thought is tagged with a stage (e.g., Problem Definition, Analysis, Ideation). If the LLM spends too long in a stage or has low-quality thoughts, the server gives feedback to steer toward other stages or different thinking strategies.

Does the server persist thoughts to a file or database?

No. Currently, all thoughts are stored only in memory. There is no user interface or persistence to a file or database.

What are the main limitations of the server?

The metacognitive monitoring is mechanical, based on a single self-reported quality score and naive stage-based multipliers. There is also no user interface or visualization of the thought graph.