An MCP server to search and crawl the web for your AI agents

# Register it with your coding agents
uvx searxncrawl setup

# or run the MCP server yourself (STDIO)
export SEARXNG_URL=http://localhost:8888
uvx searxncrawl

# or serve it over HTTP
uvx searxncrawl --transport http --port 9555

MCP tools

search      query to merged results per provider
crawl       URLs to Markdown or JSON
crawl_site  site to one Markdown document per page

# Crawl a page
crawl https://docs.example.com

# Crawl a site with limits
crawl https://docs.example.com --site --max-depth 2 --max-pages 10 -o docs/

# Search the configured providers
search "python tutorials" --max-results 5

docs/
├── index.md
├── getting-started.md
├── guides/
│   ├── auth.md
│   └── deploy.md
└── api.md

from crawler import crawl_page_async, crawl_site

# One page
doc = await crawl_page_async("https://docs.example.com/intro")
print(doc.markdown)

# A whole site
result = crawl_site("https://docs.example.com", max_depth=2, max_pages=10)
for doc in result.documents:
    print(doc.status, doc.final_url)

# Introduction

Welcome to Example Docs. This guide
walks you through installation,
configuration and your first request.

200 https://docs.example.com/
200 https://docs.example.com/intro

# MCP server with Chromium included
cp .env.example .env   # set SEARXNG_URL, YDC_API_KEY or both
docker compose up --build

# MCP endpoint
http://localhost:9555/mcp

{
  "mcpServers": {
    "crawler": {
      "url": "http://localhost:9555/mcp"
    }
  }
}