"Overview and Information on PG Vector" matching MCP servers:

Enables semantic code search over a local codebase using Qdrant vector embeddings and OpenAI embeddings, allowing natural language queries from MCP-compatible clients like Claude Desktop.

A CLI-first semantic code search tool with MCP integration for AI assistants, enabling semantic search, AST-aware parsing, and code analysis across 13 languages.

Enables semantic code search across multi-language codebases using natural language queries, integrated with Qdrant vector database for fast, cached retrieval.

locidx

MCP server with local vector search for your codebase. Smart indexing, semantic search, Git history — all offline.

A local MCP server that provides semantic code search for Python codebases using tree-sitter for chunking and LanceDB for vector storage. It enables natural language queries to find relevant code snippets based on meaning rather than just text matching.

Cartograph is an MCP server that provides agent-native code intelligence by building a queryable code graph from a repository using tree-sitter and SQLite. It offers tools for symbol lookup, call graph traversal, blast radius analysis, and architecture overview to help coding agents answer structural questions about code.

Converts vector PDF circuit schematics into evidence-preserving SchematicIR JSON with tools to inspect, convert, and validate schematic PDFs.

Enables token-efficient semantic search and analysis over any directory of files through hybrid search, directory overview, structural analysis, and dependency graphs.

A code review tool server based on Model Context Protocol (MCP), providing multi-dimensional code review and scoring functions.

Generates comprehensive documentation (architecture overview, dependency graph, API surface, and README) for any codebase locally without external APIs.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Enables AI agents to perform hybrid code search, get explanations, analyze relations and impacts, retrieve context packs, and generate documentation across ~45 languages via 17 MCP tools, all powered by a local vector database and LLM.

Enables VS Code Copilot to understand and query codebases through semantic search, call graph analysis, and related file discovery, using a local SQLite index with graph and vector embeddings.

Embeds your codebase into a local vector and graph database and exposes it as an MCP tool, enabling AI assistants to perform fast semantic search over your code using Graph RAG.

Semantic search server for code and documentation using Qdrant vector database. Supports multi-language indexing, live updates, and natural language queries.

Semantic code search engine for Claude Code with hybrid search combining vector, FTS, AST graph, and ripgrep regex, with RRF fusion and reranking.

Enables natural language queries about JavaScript/TypeScript codebases using graph and vector search. Allows finding functions by semantic description, callers, callees, and function details.

Enables AI coding agents to inspect Runable projects over MCP, providing read-only access to project information and configuration via Runable's inspector.

MCP server for semantic code search and dependency graph analysis. Indexes codebases into a knowledge graph with vector embeddings for AI-powered code understanding.