About mcp-md-vector-search
mcp-md-vector-search is a lightweight MCP server for finding similar content in local Markdown documents. It uses PGLite and pgvector for vector similarity search.
Key features
- 01Local Markdown similarity search
- 02PGLite-backed storage
- 03pgvector vector search
Use cases
- 01Finding related passages in Markdown files
- 02Searching a local Markdown collection by similarity
MCP support
It exposes similarity search over local Markdown documents to MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEmcp-md-vector-search
A lightweight MCP server implementation that leverages PGLite and pgvector to perform efficient similarity searches on local Markdown documents using the Model Context Protocol (MCP).
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.