Structured Thinking MCP Server

Structured Thinking MCP Server

By Promptly-Technologies-LLC GitHub

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
Overview

what is Structured Thinking MCP Server?

The Structured Thinking MCP Server is a TypeScript-based Model Context Protocol (MCP) server designed to enable large language models (LLMs) to programmatically create mind maps for exploring ideas, while incorporating metacognitive self-reflection.

how to use Structured Thinking MCP Server?

To use the server, configure it in an MCP client like Claude Desktop or Cursor by setting the tool configuration with the command to run the server.

key features of Structured Thinking MCP Server?

  • Thought Quality Scores to evaluate the quality of thoughts.
  • Thought Stages to manage the lifecycle of thinking processes.
  • Thought Branching to explore multiple lines of reasoning.
  • Memory Management for short-term and long-term thought storage.

use cases of Structured Thinking MCP Server?

  1. Assisting LLMs in structured problem-solving.
  2. Facilitating brainstorming sessions with multiple ideas.
  3. Enhancing creative thinking through guided thought processes.

FAQ from Structured Thinking MCP Server?

  • What is the purpose of Thought Quality Scores?

They help provide feedback to the LLM on how to improve its thinking process.

  • Can I visualize the mind map?

Currently, there is no user interface for visualization, but future updates may include this feature.

  • Is there a way to save thoughts?

Currently, thoughts are stored in memory and not persisted to a file or database.

Content

Structured Thinking MCP Server

A TypeScript Model Context Protocol (MCP) server based on Arben Ademi's Sequential Thinking Python server. The motivation for this project is to allow LLMs to programmatically construct mind maps to explore an idea space, with enforced "metacognitive" self-reflection.

Setup

Set the tool configuration in Claude Desktop, Cursor, or another MCP client as follows:

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

Overview

Thought Quality Scores

When an LLM captures a thought, it assigns that thought a quality score between 0 and 1. This score is used, in combination with the thought's stage, for providing "metacognitive" feedback to the LLM how to "steer" its thinking process.

Thought Stages

Each thought is tagged with a stage (e.g., Problem Definition, Analysis, Ideation) to help manage the life-cycle of the LLM's thinking process. In the current implementation, these stages play a very important role. In effect, if the LLM spends too long in a given stage or is having low-quality thoughts in the current stage, the server will provide feedback to the LLM to "steer" its thinking toward other stages, or at least toward thinking strategies that are atypical of the current stage. (E.g., in deductive mode, the LLM will be encouraged to consider more creative thoughts.)

Thought Branching

The LLM can spawn “branches” off a particular thought to explore different lines of reasoning in parallel. Each branch is tracked separately, letting you manage scenarios where multiple solutions or ideas should coexist.

Memory Management

The server maintains a "short-term" memory buffer of the LLM's ten most recent thoughts, and a "long-term" memory of thoughts that can be retrieved based on their tags for summarization of the entire history of the LLM's thinking process on a given topic.

Limitations

Naive Metacognitive Monitoring

Currently, the quality metrics and metacognitive feedback are derived mechanically from naive stage-based multipliers applied to a single self-reported quality score.

As part of the future work, I plan to add more sophisticated metacognitive feedback, including semantic analysis of thought content, thought verification processes, and more intelligent monitoring for reasoning errors.

Lack of User Interface

Currently, the server stores all thoughts in memory, and does not persist them to a file or database. There is also no user interface for reviewing the thought space or visualizing the mind map.

As part of the future work, I plan to incorporate a simple visualization client so the user can watch the thought graph evolve.

MCP Tools

The server exposes the following MCP tools:

capture_thought

Create a thought in the thought history, with metadata about the thought's type, quality, content, and relationships to other thoughts.

Parameters:

  • thought: The content of the current thought
  • thought_number: Current position in the sequence
  • total_thoughts: Expected total number of thoughts
  • next_thought_needed: Whether another thought should follow
  • stage: Current thinking stage (e.g., "Problem Definition", "Analysis")
  • is_revision (optional): Whether this revises a previous thought
  • revises_thought (optional): Number of thought being revised
  • branch_from_thought (optional): Starting point for a new thought branch
  • branch_id (optional): Identifier for the current branch
  • needs_more_thoughts (optional): Whether additional thoughts are needed
  • score (optional): Quality score (0.0 to 1.0)
  • tags (optional): Categories or labels for the thought

revise_thought

Revise a thought in the thought history, with metadata about the thought's type, quality, content, and relationships to other thoughts.

Parameters:

  • thought_id: The ID of the thought to revise
  • Parameters from capture_thought

retrieve_relevant_thoughts

Retrieve thoughts from long-term storage that share tags with the specified thought.

Parameters:

  • thought_id: The ID of the thought to retrieve relevant thoughts for

get_thinking_summary

Generate a comprehensive summary of the entire thinking process.

clear_thinking_history

Clear all recorded thoughts and reset the server state.

License

MIT

No tools information available.
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