Neuro V2

Description

Neuro MCP V2 is an advanced, production-grade local Model Context Protocol (MCP) server designed specifically for Claude Desktop. It supercharges Claude with a suite of agentic capabilities, bridging the gap between local execution and AI assistance using standard I/O (stdio) transport.

Key Features

• Persistent Semantic Memory: Utilizes local embedded ChromaDB to store, embed, and instantly recall user context and project insights across different chat sessions.
• Sandboxed File System I/O: Safely reads and writes files asynchronously via aiofiles within a strict, path-traversal-protected workspace/ directory.
• Live Web Research: Interacts with the Tavily Search API via httpx to pull real-time data, documentation, and news directly into Claude's context window.
• Local Emotional Intelligence: Runs a localized Hugging Face DistilRoBERTa pipeline via transformers and torch to analyze the semantic emotional tone of text blocks with zero external API latency.
• Algorithmic Text Summarization: Compresses long documents and web search dumps using an extractive summarization engine based on normalized word-frequency scoring, instantly extracting key informational sentences to prevent LLM context window exhaustion.
• Zero-Dependency Entity & Intent Extraction: Parses unstructured text records locally using a highly optimized, regex-based NLP engine to instantly extract critical parameters (IPs, emails, URLs, monetary bounds) and classify system operational intent.

Architecture & Tech Stack

• Framework: fastmcp (Official Python SDK for MCP)
• Package Management: uv (Fast Python dependency resolution)
• Database: chromadb (Serverless, local SQLite vector storage)
• Machine Learning: transformers, torch
• Async Operations: aiofiles, httpx

Project Structure

neuro_mcp_v2/
├── .venv/
├── memory_db/             
├── workspace/     
├── .python-version
├── README.md
├── main.py
├── pyproject.toml
├── src/
    ├── mymcp/
        ├── server.py
        ├── tools/
            ├── emotion.py
            ├── fs_io.py
            ├── memory.py
            ├── websrch.py
            ├── extractor.py
            ├── summarize.py
        ├── utils/
            ├── security.py
├── uv.lock

Prerequisites

• Python: 3.10 or higher
• Claude Desktop Application
• Tavily API Key: For web search capabilities

Installation

Clone the repository and navigate to the project root. Sync the dependencies using uv:

uv sync

Crucial Pre-flight Step: Run the server manually once to cache the Hugging Face emotion model (~300MB) locally and prevent Claude Desktop initialization timeouts:

uv run src/mymcp/server.py

Press Ctrl + C once the model finishes downloading.

Claude Desktop Configuration

To connect this server to Claude, edit your Claude Desktop configuration file (located at %APPDATA%\Claude\claude_desktop_config.json on Windows). [or simply go to Claude Desktop -> profile -> settings -> developer -> edit config option(if the mcp option is not shown automatically) -> make changes to the file that opens] Point the command to your project's absolute path and supply your API keys in the environment block:

{
  "mcpServers": {
    "neuro-mcp-v2": {
      "command": "C:\\Absolute\\Path\\To\\second_mcp_server\\.venv\\Scripts\\python.exe",
      "args": [
        "C:\\Absolute\\Path\\To\\second_mcp_server\\src\\mymcp\\server.py"
      ],
      "env": {
        "PYTHONUTF8": "1",
        "TAVILY_API_KEY": "your_tavily_api_key_here"
      }
    }
  }
}

Restart Claude Desktop entirely after updating this file. You should see the MCP plug icon appear in your chat window.

Security Notice

This application includes a workspace/ sandbox. The security middleware prevents the AI from reading or writing files outside of this specific directory to protect your local machine. Do not bypass the security.py checks.

License

This project is licensed under the MIT License.