Skip to main content

MCP (Model Context Protocol) Server implementation that provides AI tools to search using YaCy web search API

Project description

YaCy MCP Server

MCP (Model Context Protocol) Server implementation that provides AI tools to search using YaCy web search API.

Installation

  1. Make sure you have uv installed:
pip install uv
  1. Install the package in development mode:
cd yacy-mcp
uv sync  # Sync all dependencies from pyproject.toml and uv.lock

Or alternatively:

cd yacy-mcp
uv pip install -e .

Usage

  1. Make sure you have a YaCy server running (typically on http://localhost:8090)
  2. Set environment variables (optional):
export YACY_URL=http://localhost:8090
  1. Run the MCP server:
python -m yacy_mcp

Configuration

The server can be configured using environment variables:

Available Tools

  • yacy-search: Search using YaCy web search engine
    • Parameters:
      • query (string, required): Search query string
      • max_results (integer, optional): Maximum number of results to return (default: 10)
      • resource (string, optional): Search resource (local or global, default: global)

MCP Configuration for AI Applications

To use this server with AI applications that support the Model Context Protocol (MCP), configure your MCP client to connect to the server using stdio transport.

Example configuration for Claude Desktop (settings.json):

{
  "mcpServers": {
    "yacy-mcp": {
      "command": "uvx",
      "args": ["yacy_mcp"],
      "env": {
        "YACY_URL": "http://localhost:8090"
      }
    }
  }
}

For other MCP-compatible applications, use the command uvx yacy_mcp as the server executable. The server will be automatically fetched and run from PyPI.

Integration with AI Applications

This MCP server can be used with AI applications that support the Model Context Protocol to perform web searches using the YaCy search engine.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

yacy_mcp-0.1.0.tar.gz (54.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

yacy_mcp-0.1.0-py3-none-any.whl (4.4 kB view details)

Uploaded Python 3

File details

Details for the file yacy_mcp-0.1.0.tar.gz.

File metadata

  • Download URL: yacy_mcp-0.1.0.tar.gz
  • Upload date:
  • Size: 54.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.7

File hashes

Hashes for yacy_mcp-0.1.0.tar.gz
Algorithm Hash digest
SHA256 ca786f4e73654291569020e503a1f581c511265c2b0763796de77875588e378c
MD5 4766552e7dd1256ad93cfcc00ae9672d
BLAKE2b-256 03ba8dc3e73a3bd3e6110e275dca681152fa8bde4ff5bf788487fe10540ebf11

See more details on using hashes here.

File details

Details for the file yacy_mcp-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: yacy_mcp-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 4.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.9.7

File hashes

Hashes for yacy_mcp-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 88defe7943b135478f753933600fb37d5891e94bc40f3fadfd58c5868ca75336
MD5 ba505462533c9b7daa4755145027e762
BLAKE2b-256 fcd206dd826d0579c21fe0733fa80a7a6cc745f40cb5806116a6679f6b9fd566

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page