yacy-mcp
Enables AI applications to perform web searches using a YaCy search engine instance through the Model Context Protocol.
README
YaCy MCP Server
MCP (Model Context Protocol) Server implementation that provides AI tools to search using YaCy web search API.
Installation
- Make sure you have
uvinstalled:
pip install uv
- 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
- Make sure you have a YaCy server running (typically on http://localhost:8090)
- Set environment variables (optional):
export YACY_URL=http://localhost:8090
- Run the MCP server:
python -m yacy_mcp
Configuration
The server can be configured using environment variables:
YACY_URL: URL of your YaCy instance (default: http://localhost:8090)
Available Tools
yacy-search: Search using YaCy web search engine- Parameters:
query(string, required): Search query stringmax_results(integer, optional): Maximum number of results to return (default: 10)resource(string, optional): Search resource (local or global, default: global)
- Parameters:
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.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.