"Vector Database" matching MCP servers:

MCP server that parses 3GPP .docx specifications into structured sections with full-text search, letting LLMs browse, search, and follow cross-references without a vector database.

Enables AI assistants to manage and query Tiger Cloud database services, including service lifecycle operations, database connections, and SQL execution.

Enables AI assistants to explore a PostgreSQL database, run bounded read-only SQL, inspect query plans, test hypothetical indexes, find slow queries, and check database health with compact CSV output.

MCP-Server from your Database optimized for LLMs and AI-Agents. Supports PostgreSQL, MySQL, ClickHouse, Snowflake, MSSQL, BigQuery, Oracle Database, SQLite, ElasticSearch, DuckDB

The Multi DB MCP Server is a high-performance implementation of the Database Model Context Protocol designed to revolutionize how AI agents interact with databases. Currently supporting MySQL and PostgreSQL databases.

MCP server for GLEIF LEI (Legal Entity Identifier) database access. Look up, validate, and search legal entities and their relationships in the global LEI system.

Enables querying GeoIP2, GeoLite2, and custom MMDB databases through the Model Context Protocol for IP lookups, filtered network queries, resumable pages, and MaxMind database downloads.

Coordination for parallel coding agents: TTL file claims stored in the git common dir (visible across all worktrees), enforcement hooks that block colliding edits, agent presence, handoff notes, and a git-committed lessons knowledge base with BM25 search. Single static Go binary — no server, no database.

Local-first MCP server providing semantic search over library docs, fully offline. Single Go binary speaks MCP over stdio against a vector index pinned to the binary version. Like Context7 with the internet turned off. Apache 2.0. Linux + macOS, also available as a container image.

I gave Claude a mass grave of 200 markdown files and now it remembers my entire project between sessions. No cloud, no API keys, one 10mb Go binary, and private. Stateless Agent Memory Engine is your synapse to the CLI.

Enables managing and controlling AnythingLLM instances through MCP, providing tools to list, create, and delete workspaces, retrieve system environment settings, and get vector counts.

A persistent, Git-versioned map of your whole codebase and database schema that coding agents read before they touch anything. Local-first MCP server + CLI in Go: a governed repository index of code knowledge that gives Claude Code, Codex, Cursor, and opencode long-term context, memory, and code intelligence.

Local-first, git-synced memory and system of records for AI agents: a signed append-only event log projected into graph, vector and full-text indexes, with hybrid recall and provenance on every fact.

WhoDB CLI - a powerful database management tool with interactive TUI, programmatic commands, and MCP server for AI assistants.

Fraise is a memory database for AI agents. Agents can autonomously manage what's saved and retrieve memory with a simple query language

Bridges MCP clients that require stdio to a running pREST HTTP MCP endpoint, enabling database interaction via natural language.

Enables AI tools to query a PostgreSQL database, read its schema, list and describe tables, and explain queries while enforcing read-only transactions, row and byte limits, and timeouts.

Connect to your TTRPG campaign's repository and database. Instead of retrieving prose, its 48 tools (20 read, 28 write) return typed state: 14 entity schemas (NPCs, factions, locations, sessions, lore), relationship and knowledge-graph queries, wiki blocks, and a narrative-state bundle of open threads and canon facts.

Enables AI agents to review and compare Go goroutine dumps, surfacing goroutine leaks, lock pile-ups, exhausted database pools, and missing HTTP timeouts from dump text alone without connecting to the service.

Production-ready MCP server designed to empower AI agents and LLMs to interact seamlessly with ClickHouse. It exposes your ClickHouse database as a set of standardized tools and resources that adhere to the MCP protocol, making it easy for agents built on OpenAI, Claude, or other platforms to query, explore, and analyse your data.

Enables AI agents to read and edit entity-relationship diagrams and SQL database schemas on the liz-whiteboard collaborative whiteboard through natural language, supporting table, column, and relationship management.

Provides a read-only schema extraction tool that converts database structures from numerous dialects into Toon format, accepting live connections or offline SQL dumps.

Shared memory and a knowledge graph for AI agents: hybrid vector and keyword search, RAG over your docs, scoped agent memory, and RDF/SPARQL and Cypher graph queries. Works without an embedding model; one server can serve many agents.

Provides AI assistants with persistent graph database memory using Neo4j, enabling task management, relationship understanding, semantic search with embeddings, file indexing, and multi-agent coordination through the Model Context Protocol.

🧠 High-performance persistent memory system for Model Context Protocol (MCP) powered by libSQL. Features vector search, semantic knowledge storage, and efficient relationship management - perfect for AI agents and knowledge graph applications.

Gives AI coding assistants, IDEs, and CI full PostgreSQL schema intelligence from an offline snapshot, enabling linting, query validation, migration safety analysis, and foreign key graph exploration without ever exposing database credentials.

Minimal long-term memory MCP server for AI assistants backed by SQLite FTS5 full-text search, optional hybrid vector retrieval, scoped memory graphs, and VSCode extension.

Enables AI agents to scan directories, container images, and SBOMs for vulnerabilities, look up individual CVEs, and refresh the local vulnerability database. Findings come back prioritized with concrete upgrade targets rather than raw scanner output.

Open source MCP server specializing in easy, fast, and secure tools for Databases.

Governed multi-agent memory for AI agents. Hybrid markdown + SQLite store with full-text search, vector retrieval, and LLM reranking. Three transports: MCP stdio, HTTP JSON-RPC, and MCP SSE. One Go binary