"Arc" matching MCP servers:

ArcadeDB Multi-Model Database, one DBMS that supports SQL, Cypher, Gremlin, HTTP/JSON, MongoDB and Redis. ArcadeDB is a conceptual fork of OrientDB, the first Multi-Model DBMS. ArcadeDB supports Vector Embeddings.

Scrapes, indexes, and serves Salesforce Architect documentation locally, enabling fast offline RAG-powered search and retrieval for AI coding assistants.

Semantic vector DB as an MCP server for Claude Code — SQLite + FTS5 + local ONNX embeddings. Gives Claude persistent, searchable project knowledge across conversations.

Serves an offline knowledge base — an aggregated corpus of reference works plus a RAG index over them and the user's own documents — to any local AI model over MCP. Enables offline assistants such as Open WebUI, OpenCode, or Jan to ground answers in searchable, provenance-tracked local content without any network connection.

Persistent memory for AI coding tools that captures conversations, builds a searchable knowledge graph, and automatically injects relevant context into new prompts.

Archive Agent is an open-source semantic file tracker with OCR + AI search (RAG) and MCP capability.

An MCP server providing semantic memory storage and retrieval using vector embeddings powered by LanceDB and Google Gemini. It supports multi-tenant isolation and bucket-based organization for managing structured memories through natural language queries.

Enables semantic search over local Calibre libraries via MCP, allowing AI assistants to query books, annotations, and export bibliographies while keeping data private.

Enables semantic search across conversation archives via MCP, allowing AI clients to retrieve relevant past conversations using vector embeddings and text fallback.

Enables AI assistants to access and query a verified knowledge base of Chinese whisky, including distillery profiles, flavor notes, product recommendations, regional maps, and content generation support.

An MCP server and CLI tool that transforms codebases into AI-ready context through semantic search, call graph analysis, and incremental indexing. It enables AI assistants to perform hybrid vector and keyword searches to understand complex repository structures and cross-file relationships.

Enables semantic search and AI-powered analysis of Outlook emails using RAG-based natural language queries and Vision AI for architectural documents, with specialized support for AEC workflows.

A high-performance memory management system for AI agents with 200+ tools including 4-tier memory architecture, advanced RAG pipeline, and Git-like versioning.

A Model Context Protocol server that helps users migrate subscription businesses from RevenueCat to Adapty through natural language interactions with LLMs like Claude Desktop.

Enables semantic search and question-answering over semiconductor component data stored in Excel files using ChromaDB vector database and HuggingFace language models through a RAG pipeline.

A high-performance MCP server that connects tools like Cursor to Elasticsearch clusters using public-key authorization instead of API keys. It provides optimized tools for searching data, listing indices, and inspecting cluster mappings or shards with support for concurrent requests.

A cognitive memory system for MCP that provides hybrid retrieval, memory layers, entity graph, and 83 tools for recall, remember, codebase scanning, and more.