"A server for semantic API information and resources" matching MCP servers:

LLM routing proxy that cuts API costs 60-90% by auto-selecting the cheapest capable model across OpenAI, Anthropic, and Google. Provides stats, config, and model comparison tools via MCP.

Local semantic recall MCP server for citation-integrity workflows. Enables semantic search over a text corpus, returning file paths and page numbers for verification, with 100% local processing using ONNX embeddings and LanceDB.

Enables MCP clients to serve and query semantic models, providing tools for entity descriptions, metric lookups, context resolution, and operation validation for AI agents.

Persistent memory with semantic search for Claude and MCP-compatible clients, storing context that survives conversations and can be retrieved intelligently.

A comprehensive Model Context Protocol server that provides AI assistants with direct access to Semantic Scholar's academic database, enabling advanced paper discovery, citation analysis, author research, and AI-powered recommendations.

MCP file cache for AI coding agents. Re-reading an unchanged file costs ~40 tokens instead of the whole file; a changed file comes back as a diff. Adds grep, BM25 search and glob over cached files, atomic edits with dry_run, and token-budgeted batch reads. One local daemon serves every client. No API keys, no GPU. Works with Claude Code, Cursor, VS Code, Codex and OpenCode.

Enables agents to query governed metrics through MCP, including describing metrics, running deterministic SQL against a warehouse, explaining join path preferences, and searching semantically ambiguous terms.

Enables natural-language semantic search of a project's code through a local vector index, so questions that plain grep cannot match return ranked file:line references. It also indexes or refreshes projects on demand, reports index status, and optionally flags near-identical code across files.

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.

Local offline semantic search over documents (txt, md, pdf, docx, pptx, csv). Indexes folders into a LanceDB vector database with multilingual embeddings and supports hybrid vector + keyword search via Reciprocal Rank Fusion. No API keys, no cloud, no Docker required.

A read-only PostgreSQL MCP server for AI coding agents that exposes database schema and sample data as tools, with LLM-powered semantic search enriched by a user-authored semantic layer.

Read-only semantic retrieval for agents that need to find the right Obsidian note without write access.

A self-hosted semantic code retrieval MCP server that enables natural language queries to find relevant code snippets using Tree-sitter AST parsing, embedding, and hybrid search with reranking.

Enables coding agents to search locally indexed repositories with hybrid semantic and lexical retrieval, returning exact source citations with file paths and line ranges.

Enables AI assistants to save, load, and search conversation context with AI-powered summarization and auto-tagging. Demonstrates semantic intent patterns and hexagonal architecture for maintainable AI-assisted development.

A persistent memory layer for Claude Desktop that enables semantic search and CRUD operations on your Obsidian vault using local embeddings and PostgreSQL+pgvector.

Enables fully local semantic search over a Roam Research graph via MCP, providing tools for hybrid retrieval, index refresh, and stats while keeping all content on-machine.

A tiny RAG-lite retrieval engine that indexes files on disk and provides semantic search via MCP, returning relevant text chunks (file, line, score) without generating answers.

An MCP server over stdio that lets agents find code by meaning using local Ollama embeddings and trace callers or callees through real tree-sitter AST parsing rather than regex or keyword matching. It shares the same search and trace engine as the companion CLI, so MCP-native agents and shell-only agents get identical, reproducible results.

Enables coding agents to persistently store memories, artifacts, and context discarded by compaction into a searchable store, then automatically recall and inject the items relevant to the current task. It fuses BM25 keyword search with embedding-vector retrieval so differently-phrased memories still match, running as a fail-open sidecar that never blocks the agent session.

Provides worktree-aware semantic code indexing and search via MCP, enabling agents to query indexed code and monitor indexing status while keeping lifecycle operations separate.

Enables semantic code search over local repositories, providing tools like semantic_search and list_indexed_repos to Claude Code, so users can find relevant code sections via natural language instead of grep.

Enables semantic search over documentation stored in a Vectorize database using the Cloudflare Agents SDK, allowing users to query indexed content via natural language.

A local semantic search MCP server for Markdown vaults that indexes and retrieves notes using hybrid keyword and embedding search.

Enables AI agents to query verified-emissions knowledge graphs in natural language and validate data against supported standards, with metered billing and optional verified identity.

Enables document Q&A with grounded citations using the official Gemini File Search API. Upload documents, create stores, and ask questions that return exact passage citations.

An MCP server that gives AI coding assistants access to up-to-date API documentation via RAG by crawling documentation sites, indexing them into a vector store, and enabling semantic queries.

An unofficial MCP server that provides semantic search capabilities for Hugging Face models and datasets, enabling Claude and other MCP-compatible clients to search, discover, and explore the Hugging Face ecosystem using natural language queries.

MCP server for Turkish legal semantic search using NVIDIA nv-embed-v1 embeddings, with rate-limit resilience and query embedding caching for fast RAG responses.

An MCP (Multi-Agent Conversation Protocol) Server that enables interaction with eBay's Sell Marketing API through natural language, auto-generated using AG2's MCP builder.