"A service that retrieves Terraform documentation via MCP" matching MCP servers:

A Model Context Protocol implementation that enables AI assistants to interact with markdown documentation files, providing capabilities for document management, metadata handling, search, and documentation health analysis.

Enables routing context and execution across AI tools like Claude, Cursor, Windsurf, and ChatGPT with a shared memory, task board, and context bus, plus local file conversion.

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

MCP server for InvGate Service Desk — manage incidents, users, knowledge base, assets and time tracking from any AI assistant.

Provides intelligent, persistent memory for AI assistants with semantic search, natural language queries, and OAuth-based team collaboration, enabling context-aware conversations across multiple clients.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

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

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 consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Enables character management and semantic search for the Auto-Movie application through WebSocket communication. Supports creating characters with personality/appearance descriptions and finding similar characters using natural language queries with embedding-based similarity matching.

Provides self-hosted, versioned project memory with full-text and vector search, enabling search, retrieval, upsertion, and history management of project entries via MCP tools.

A self-synthesizing AI knowledge wiki that provides a read-only MCP surface for external agents to trace the wiki content and graph.

A modular server that implements the Model Context Protocol standard, providing tools for interacting with GitHub, GitLab, Google Maps, Memory storage, and web automation through a unified gateway.

Free service management tools — playbooks, benchmarks, and instant service health analysis. DigitalCore MCP gives you free access to service management expertise directly in your AI assistant. Run a Service Reality Check to score your service health in 60 seconds. Access strategy playbooks for ser

Enables querying context about the MAM product components and architecture through MCP, allowing agents to retrieve targeted product information on demand instead of loading full documentation.

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.

Provides screen capture, OCR text extraction, and visual language model scene understanding capabilities with continuous monitoring and automatic memory storage integration.

Enables users to access, search, and get recommendations from AWS documentation through natural language queries. Supports both global AWS documentation and AWS China documentation with tools to fetch pages, search content, and discover related resources.

A cloud-based vector memory service that provides AI assistants with persistent storage, semantic search, and entity management via the Model Context Protocol. It features multi-tenant isolation and bidirectional synchronization with macOS and Google contacts and calendars.

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

An MCP server for managing notes, with resources, prompts, and a tool to add notes.

Enables semantic search and management of development knowledge including global rules, project documentation, and references through vector-based search using libSQL. Features Tailscale-secured access control and tools for searching, browsing, and organizing development resources across multiple channels.

An MCP server implementation that helps Claude remember and learn from programming errors by storing, retrieving, and finding similar errors with full context.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

An open-source bitemporal knowledge graph that provides long-term memory for AI agents via a native MCP endpoint, enabling conflict-aware ingest and hybrid retrieval.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.

Connects AI assistants to Obsidian vaults via the Local REST API to search notes, retrieve content, and perform semantic searches. It features self-healing multi-URL connectivity and supports both stdio and HTTP transports for flexible deployment.

Enables AI-powered multi-provider routing and chat through an MCP interface, with smart fallback, persistent sessions, and learning from historical performance.

An open-source MCP server that provides applications like Cursor, Windsurf, and Claude with access to llms.txt documentation files, allowing users to control and audit context retrieval.