"database" matching MCP servers:

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.

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

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

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.

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.

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.

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.

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.

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.

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.

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.

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.