"Finding API Documentation for METRC" matching MCP servers:

Provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.

An MCP server that provides AI assistants with access to Multi Theft Auto: San Andreas function documentation through vector similarity search and smart keyword expansion. It enables efficient information retrieval with features like deprecation warnings and SQLite caching for technical documentation.

Enables AI assistants to enhance their responses with relevant documentation through a semantic vector search, offering tools for managing and processing documentation efficiently.

Enables AI agents to intelligently search and retrieve Roblox documentation through semantic search and vector embeddings, providing natural language access to complete Roblox Creator Documentation.

An Agent Framework Documentation server that enables AI agents to efficiently retrieve information from documentation databases using hybrid semantic and keyword search for seamless agent integration.

Enables semantic search and retrieval of MCP (Model Context Protocol) documentation using Redis-backed embeddings, allowing users to query and access documentation content through natural language.

A Machine Control Protocol (MCP) server that enables storing and retrieving information from a Qdrant vector database with semantic search capabilities.

An integration server implementing the Model Context Protocol that enables LLM applications to interact with Milvus vector database functionality, allowing vector search, collection management, and data operations through natural language.

Enables semantic search over OpenAPI endpoint catalogs using FAISS and LangGraph, returning grounded technical recommendations for natural-language API queries.

Provides semantic search and complete document retrieval by ID through OpenAI's Vector Store API, letting deep research agents access company-specific knowledge and tools.

Enables users to ingest documents into a PostgreSQL/pgvector knowledge base, run semantic search over them, and get grounded answers through a retrieval-augmented generation pipeline backed by a free LLM. It also lets clients spin up specialized AI agents on demand and exposes knowledge-base stats and configuration as resources for tutoring workflows.

A local-first Graph-RAG system combining ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q&A over Obsidian vaults, supporting MCP clients like Claude Desktop, Cursor, and Raycast.

A server implementation that allows secure communication between MCP clients and privateGPT, enabling users to chat with privateGPT using knowledge bases and manage sources, groups, and users through a standardized Model Context Protocol.

Enables stateless similarity search over pre-computed vector corpora using NMI and cosine fusion with entropy-calibrated weighting. Provides tools for ranking, scoring, outlier detection, and alpha calibration for AI agents.

Munin is a high-performance, pragmatic memory layer for AI agents (Cursor, Claude Code, OpenClaw, Gemini CLI,...). Unlike other solutions, Munin focuses on developer productivity with: * Multi-Project Support: Isolate memories into separate "brains" (Context Cores). * GraphRAG: Automatically builds a knowledge graph from your context. * Sub-200ms Search: Blazing fast Hybrid & Semantic

A local Retrieval-Augmented Generation system that enables users to ingest markdown files into a FAISS-powered vector knowledge base for semantic search. It provides tools for document indexing and context retrieval to support informed LLM queries without external dependencies.

Provides semantic search over AWS Cloudscape Design System documentation using natural language queries, enabling AI assistants to efficiently find and retrieve component documentation with token-efficient responses.

MCP server for OpenAI Vector Store API, managing vector stores, files, file batches, and semantic search.

Enables LLM hosts to retrieve live, relevant documentation excerpts from official library docs sites via a search-and-RAG tool, avoiding reliance on training data.

Self-hosted Mem0 MCP server integrating Qdrant, Neo4j, and Ollama for semantic memory search, graph entity relationships, and memory management via OpenMemory API.

A local-first knowledge base for LLM coding agents that indexes repository documentation, concept ontology, and build targets into Qdrant and exposes retrieval as MCP tools (search, get, list sources, reindex).

Lets AI assistants connect to Apache Solr deployments to enumerate collections and schemas, run full-text and filtered queries, apply faceting and sorting, and issue SQL or vector-semantic searches without building custom API glue. Communicates over stdio or SSE and requires minimal environment configuration instead of app-specific credentials or mandatory ZooKeeper wiring.

An MCP server that integrates with LangChain and ChromaDB to provide documentation search for AI libraries and vector database management.

Integrates R2R (Retrieval-Augmented Generation) with Claude Desktop, enabling semantic search across knowledge bases and RAG-based question answering with support for vector, graph, web, and document search.

Provides Claude Code read-only access to PostgreSQL for relational queries, schema inspection, EXPLAIN plans, pgvector similarity searches, and Apache AGE graph traversals.

Enables Claude Desktop to search, add, list, retrieve, reinforce, and delete memories through a remote HTTP memory API, with hierarchical sector classification such as episodic, semantic, and procedural. It also supports connectivity health checks and optional API key authentication for the backing graph and vector store.

A Model Context Protocol server for reading TiDB RAG knowledge base, enabling browsing, searching, and vector search of knowledge entries.

Enables making REST API calls to Teradata cloud services including Elastic Compute, Vector Store, OMS, and QueryGrid. Supports custom authentication, Socks5 proxy, and multipart file uploads.

Local-first memory for Claude Code and any MCP client: hybrid vector + keyword search and a bi-temporal knowledge graph in one SQLite file. Local embeddings, no API key, $0/token.

A server that enables vector and keyword search capabilities in Typesense databases through the Model Context Protocol, providing tools for collection management, document operations, and search functionality.