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MCP-Server com CoConuT (Continuous Chain of Thought)

@MarceloAssis123

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stdio

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MarceloAssis123

关于 MCP-Server com CoConuT

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MCP-Server com CoConuT 配置

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MCP-Server com CoConuT 工具

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概览

What is MCP-Server com CoConuT (Continuous Chain of Thought)?

An MCP server that provides the CoConuT tool for structured continuous chain-of-thought reasoning, with automatic cycle detection, branch management, and guided interaction. It is designed for developers using the Model Context Protocol to enhance models’ reasoning capabilities.

How to use MCP-Server com CoConuT (Continuous Chain of Thought)?

Clone the repository, install dependencies (npm install), configure settings in src/config.ts, then run with npm run dev for development or npm run build && npm start for production. The server exposes three tool variants: CoConuT (JSON), CoConuT‑MD (Markdown), and CoConuT‑HTML.

Key features of MCP-Server com CoConuT (Continuous Chain of Thought)

  • Continuous chain‑of‑thought for structured problem solving
  • Automatic cycle detection using Levenshtein, Jaccard, or Cosine similarity
  • Branch management: explore, compare, and merge reasoning paths
  • Periodic reflection every reflectionInterval thoughts
  • Built‑in persistence of all reasoning data
  • Multiple output formats: JSON, Markdown, HTML
  • Modular architecture with dependency injection

Use cases of MCP-Server com CoConuT (Continuous Chain of Thought)

  • Structuring long‑term reasoning tasks with continuous chain‑of‑thought
  • Detecting and avoiding circular reasoning in model outputs
  • Exploring multiple solution branches and comparing them
  • Automatically reflecting on progress during problem‑solving

常见问题

1

What is the CoConuT tool?

CoConuT (Continuous Chain of Thought) is a tool that facilitates structured, step‑by‑step reasoning with automatic cycle detection, branch management, and guided user interaction.

2

What are the runtime dependencies?

Node.js 18 or higher and NPM are required.

3

How does cycle detection work?

The system uses similarity algorithms (Levenshtein, Jaccard, Cosine) with a configurable threshold (default 0.8) to detect cyclic reasoning.

4

Where are data persisted?

All data is automatically saved to a `coconut-data` folder inside the directory specified by the `projectPath` parameter.

5

What output formats are supported?

Three tool variants return results in JSON (CoConuT), Markdown (CoConuT‑MD), or structured HTML (CoConuT‑HTML).

6

Can I change the similarity algorithm?

Yes. The `similarityAlgorithm` configuration option accepts `'levenshtein'` (default), `'jaccard'`, or `'cosine'`.

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