MCP (Model Context Protocol) Server implementation that provides AI tools to search using YaCy web search API.
Connect Yacy MCP to Claude, Cursor or any other MCP client and it stops being a tab you switch to. MCP (Model Context Protocol) Server implementation that provides AI tools to search using YaCy web search API. The yacy mcp mcp server is what makes that connection.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
yacy-search — Search using YaCy web search engineParameters — - query (string, required): Search query stringConfiguration is passed through the environment: YACY_URL. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Installation goes through your MCP client rather than a global install: point it at yacy_mcp on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
This sits in the search and retrieval group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Yacy MCP's toolset — yacy-search, Parameters — is a fair guide to whether it matches your workflow. It is maintained by koosty; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against Yacy MCP's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| yacy-search | Search using YaCy web search engine |
| Parameters | - query (string, required): Search query string |
{
"mcpServers": {
"yacy-mcp": {
"command": "uvx",
"args": ["yacy_mcp"],
"env": {
"YACY_URL": "http://localhost:8090"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| YACY_URL | Endpoint or connection string the server talks to. | Yes |
The simplest web tool that matters — fetch any URL and get model-ready markdown back.
Industrial-strength web extraction — render, scrape, crawl and search entire sites into clean markdown.
Puppeteer-powered browser control that drives pages from the accessibility tree instead of pixels.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Put 6,000+ pre-built scrapers at your assistant's fingertips through one MCP endpoint.