RAT MCP Server (Node.js)
Retrieval Augmented Thinking MCP Server - A reasoning tool that processes structured thoughts with metrics, branching, and revision capabilities.
Installation
Simple 3-Step Process
Verify Installation
Test that the installation worked:
Success indicator: If you see RAT MCP Server (Node.js) running on stdio
, your installation is ready!
Claude Desktop Configuration
Add to your Claude Desktop configuration file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%/Claude/claude_desktop_config.json
After adding the configuration, restart Claude Desktop to load the RAT server.
Usage
The server provides a single rat
tool for processing structured thoughts:
Tool Parameters
Required
thought
(string): The thought content to processnextThoughtNeeded
(boolean): Whether another thought is needed to continuethoughtNumber
(integer): Current thought number in the sequencetotalThoughts
(integer): Total expected thoughts (adjustable)
Optional
isRevision
(boolean): Whether this revises a previous thoughtrevisesThought
(integer): The thought number being revisedbranchFromThought
(integer): Thought number to branch frombranchId
(string): Unique identifier for this branchneedsMoreThoughts
(boolean): Extend beyond totalThoughts if needed
Response Format
Troubleshooting
If Installation Fails
The installation process includes automatic permission fixes. If you encounter issues:
- Ensure you have Node.js and npm installed
- Try the alternative installation method:
- For rare permission issues:
Verification Steps
Before configuring Claude Desktop, always verify:
If this shows "RAT MCP Server (Node.js) running on stdio", you're ready to configure Claude Desktop.
Testing
Run the test suite:
Test tool execution:
License
This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.
通过结构化、检索增强的思维过程增强人工智能模型能力,实现动态思维链、并行探索路径和递归细化循环,从而提高推理能力。
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