Provides semantic search capabilities for MCP documentation using Redis embeddings, enabling document search, listing, and content retrieval.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Semantic search server for MCP (Model Context Protocol) documentation using Redis embeddings.
Related MCP server: Markdown RAG MCP
python -m venv venv
source venv/bin/activate
pip install -r requirements.txtScrape documentation: python url_scraper.py
Create embeddings: python embed_to_redis.py
Run MCP server: python doc_mcp_server.py
search_docs - Semantic search through documentation
list_documents - List all available documents
fetch_file - Retrieve specific file content
{
"mcpServers": {
"doc-embeddings": {
"command": "bash",
"args": ["-c", "cd /path/to/mcp/server && source venv/bin/activate && python doc_mcp_server.py"],
"env": {}
}
}
}url_scraper.py - Scrapes MCP from mcp and convert to markdown
embed_to_redis.py - Creates embeddings from headings and stores in Redis
doc_mcp_server.py - FastMCP server providing search functionality
repo_scraper.py - Processes code repositories to markdown
output/ - Processed documentation files
This server cannot be deployed
Team docs served to AI agents over MCP - search, Markdown reads, version pinning, read audit.
The Needle MCP server enables semantic search on documents stored in files like PDFs, DOCX, and XLSX by connecting AI applications to external data sources. It provides capabilities to create and manage document collections, perform natural language searches on stored content, and retrieve relevant information without requiring exact keyword matches.
MCP server for querying Forkast documentation
Versioned documentation registry and semantic search for AI tools and coding assistants.
