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2024-12-14

Recherche de code alimentée par AI serveur MCP Utilisation de l'API EXA pour la recherche et la récupération de code intelligents dans les assistants d'IA

3 years

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Exa MCP Server

An MCP (Model Context Protocol) server that provides AI-powered code search capabilities using the Exa API.

Features

  • Perform AI-powered code searches using natural language queries
  • Get relevant code examples and documentation
  • Configurable number of search results
  • JSON response format with rich metadata

Installation

  1. Clone this repository:
git clone https://github.com/it-beard/exo-server.git
cd exa-server
  1. Install dependencies:
npm install
  1. Build the project:
npm run build
  1. Configure your Exa API key in the MCP settings file (tested with Cline):
{
  "mcpServers": {
    "exa": {
      "command": "node",
      "args": ["/path/to/exa-server/build/index.js"],
      "env": {
        "EXA_API_KEY": "your-api-key-here"
      }
    }
  }
}

Usage

The server provides the following tools and resources:

Tools

search

Perform an AI-powered search using Exa API

Input Schema:

{
  "query": "Search query",
  "numResults": 10
}

Resources

  • exa://search/{query} - Search results for a specific query
  • exa://last-search/result - Results from the most recent search query

Development

  1. Make your changes in the src directory
  2. Build the project:
npm run build
  1. Test your changes by configuring the server in your MCP settings

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

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    Reviews

    4 (1)
    Avatar
    user_sXA7kQGy
    2025-04-15

    PubMed Analysis MCP Server by Darkroaster is a game-changer for researchers. Its user-friendly interface and powerful features streamline PubMed data analysis, making it incredibly efficient. The seamless integration and robust performance save time and enhance productivity. Highly recommended for anyone involved in medical and scientific research!