"A service or resource for finding a coding expert" matching MCP servers:

Enables any MCP-compatible AI assistant to search, filter, and retrieve information from a local document collection using a hybrid search pipeline with vector, BM25, reranking, and LLM enrichment.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables hybrid retrieval over interpretable Gemini documentation knowledge graphs through eight MCP tools, combining vector, keyword, and graph-boosted search with deprecation filtering.

MCP server for a personal knowledge graph running on Cloudflare, enabling note-taking, task management, and cross-domain recall via Claude.

MCP server that studies a folder of code repositories, generates markdown documentation (architecture, interfaces, activity), and serves answers over MCP with live ripgrep search and file reads so AI assistants can query codebases and their relationships.

Builds a queryable knowledge graph from a pack of repos, papers, and notes, and serves it to agents via MCP, enabling search, source reading, and neighbor exploration.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

A high-performance MCP server for expert discovery, registration, and context injection, enabling AI-powered expert selection through semantic search and relationship modeling with vector and graph database integration.

Provides semantic memory and persistent storage for Claude, leveraging ChromaDB and sentence transformers for enhanced search and retrieval capabilities.

Enables AI assistants to search codebases by meaning using local AI embeddings, manage indexing and caching, switch workspaces, check server status, and look up latest package versions across multiple ecosystems.

Enables AI assistants to search local codebases semantically by meaning, automatically indexing code and returning relevant chunks even when terminology differs. It also supports package version lookup, workspace switching, reindexing, cache clearing, and server status checks.

Enables AI assistants to search codebases by meaning using local AI embeddings, along with package version lookup and runtime workspace, cache, indexing, and status management.

A Python-based MCP server that enables document-based question answering by processing PDF, TXT, and Markdown files through OpenAI's API. It provides hallucination-free responses based strictly on document content using semantic search and includes a web interface for management.

Enables document-based question answering using OpenAI's GPT-4 with semantic search and embeddings. Upload PDF, TXT, or Markdown files and get answers strictly based on document content with source attribution and confidence scores.

Enables AI assistants to search a codebase by meaning rather than exact keywords by indexing files with local AI embeddings, alongside package-version lookup and index management tools. It supports incremental, resource-throttled indexing across multiple workspaces and IDE integrations.

Enables AI coding assistants to search a local codebase semantically using AI embeddings, finding relevant code by meaning instead of exact keywords. It also provides package version lookup, manual reindexing, cache clearing, workspace switching, and server health status tools.

Provides hybrid retrieval (dense + BM25 + RRF) with collection-based isolation and document ingestion for private knowledge access via MCP.

Enables AI assistants to search a codebase by meaning using local AI embeddings, finding relevant code even when terminology differs from the query. Also provides package version lookup across 20+ registries, workspace switching, reindexing, cache clearing, and status checks.

Enables AI coding assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when terminology differs from the query, along with package version lookup, reindexing, cache reset, workspace switching, and status tools. Indexing runs progressively in the background with CPU throttling and a SQLite cache, letting searches work immediately on large projects.

This MCP server enables employees to ask IT questions, receive evidence-backed answers, and trigger traceable work orders or escalations through authenticated MCP tools. It also supports status checks, durable action jobs, and auditable work-order, Excel ledger, and escalation workflows.

Enables AI assistants to search code by meaning using local AI embeddings, and provides package version lookup, reindexing, cache management, workspace switching, and server status tools.

Enables AI coding assistants to find relevant code by meaning through local AI embeddings and an indexed codebase, so searches work even when terminology differs. It also supports package-version lookup, reindexing, cache management, workspace switching, and server status checks.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, with tools for indexing, cache and workspace management, status checks, and latest package-version lookup.

Enables AI coding assistants to search codebases by meaning using local AI embeddings, and provides tools for package version lookup, reindexing, cache clearing, workspace switching, and status checks.

Enables AI assistants to perform semantic code search across local codebases using AI embeddings, with support for indexing, cache management, workspace switching, status checks, and package version lookup.

Enables AI assistants to search a codebase by meaning using locally generated embeddings, so relevant code is found even when the query's wording differs from the code. It also supports package version lookups across many ecosystems, plus reindexing, cache clearing, workspace switching, and server health checks.

Enables AI assistants to search codebases by meaning using local semantic embeddings, and provides tools for package version lookup, reindexing, cache clearing, workspace switching, and server status.

Enables AI assistants to search codebases by meaning using local AI embeddings, and also provides package version lookup, indexing, cache management, workspace switching, and server status tools.

Self-hosted service providing unified memory search and write operations across file-based memory, vector embeddings, and the Graphiti temporal knowledge graph, accessible via HTTP API or MCP stdio transport.

Enables AI assistants to perform intelligent semantic code search across a codebase and provides auxiliary tools for package version lookup, reindexing, cache clearing, workspace switching, and server status checks.