mcp-crawl4ai2vectordb
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@mcp-crawl4ai2vectordbcrawl the FastAPI docs at https://fastapi.tiangolo.com"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
mcp-crawl4ai2vectordb
MCP server for crawling web documentation and storing it in a Supabase vector database. Credits: craw4ai and Cole Medin's mcp server.
Responsibility: ingestion only — crawl, chunk, embed, store. No search, no reranking, no Neo4j.
Tools
Tool | Description |
| Crawl one URL and store its content |
| Auto-detect URL type (sitemap / txt / webpage) and crawl accordingly |
| List all sources stored in the database |
| Delete a source and all its content from the database |
Related MCP server: web-docs-mcp
Setup
cp .env.example .env
# fill in OPENAI_API_KEY, MODEL_CHOICE, SUPABASE_URL, SUPABASE_SERVICE_KEY
uv syncRunning
stdio (recommended — Claude Code manages the process):
Add to your MCP config:
{
"mcpServers": {
"crawl4ai2vectordb": {
"type": "stdio",
"command": "uv",
"args": ["run", "python", "-u", "src/server.py"],
"cwd": "/path/to/mcp_crawl4ai2vectordb"
}
}
}or
{
"mcpServers": {
"crawl4ai2vectordb": {
"type": "sse",
"url": "http://localhost:8051/sse"
}
}
}SSE (manual startup, for multi-client use):
TRANSPORT=sse uv run python -u src/server.pyOptional features
Env var | Default | Effect |
|
| Prepend LLM-generated context to each chunk before embedding (improves retrieval accuracy, costs more) |
|
| Extract code blocks and store them separately in |
This server cannot be installed
Maintenance
Resources
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If you are the server author, to access and configure the admin panel.
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- Alicense-qualityDmaintenanceA database-agnostic MCP server that integrates web crawling with Retrieval Augmented Generation, supporting multiple AI providers and vector database backends for flexible and intelligent content retrieval.1MIT
- Flicense-qualityDmaintenanceDocumentation crawler MCP server that crawls and indexes documentation sites so that any MCP-compatible AI can search, read, and expand on the content.1
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