MCP Servers
Connectors that give your AI agent hands — databases, browsers, email, payments, and every service in between.
✓ Official
31 companiesPublished by the companies themselves — pick one to see everything they ship.
modelcontextprotocol10 servers
google2 servers
googleapis3 servers
microsoft3 servers
azure3 servers
github1 server
awslabs34 servers
bytedance2 servers
stripe1 server
cloudflare2 servers
vercel5 servers
figma1 server
makenotion1 server
atlassian1 server
redis2 servers
elastic1 server
jetbrains1 server
ibm3 servers
getsentry3 servers
grafana1 server
hashicorp2 servers
firebase1 server
browserbase1 server
apify1 server
mendableai1 server
clickhouse1 server
neondatabase1 server
upstash2 servers
qdrant2 servers
e2b-dev1 server
exa-labs3 serversCoreMCP
★ 10Connect Legacy Databases to AI Agents via Model Context Protocol. Open-source bridge for LLM data analysis.
DBeast
★ 10Expert-level PostgreSQL database analysis MCP server for AI assistants.
MySQL DB
★ 9An MCP server for integrating with and managing MySQL databases.
Zero-Vector MCP
★ 9A high-performance vector database server for AI persona memory management.
SchemaFlow
★ 9Real-time PostgreSQL & Supabase database schema access for AI-IDEs via Model Context Protocol. Provides live database context through secure SSE connections with three powerful tools: get_schema, analyze_database, and check_schema_alignment.
Gremlin
★ 9Interact with any Gremlin-compatible graph database using natural language, with support for schema discovery, complex queries, and data import/export.
MySQL Server
★ 9A server for performing MySQL database operations.
PubChem MCP Server
★ 9Provides comprehensive access to PubChem's chemical information database via the PubChem PUG REST API.
MongoDB
★ 9Provides read-only access to MongoDB databases through standardized MCP tools and resources.
Teradata MCP Server
★ 9Interact with Teradata databases for data queries and business intelligence.
Model Database Protocol
★ 8Intent-based, secure database access protocol for AI systems — LLMs send structured intents instead of raw SQL.
Node MSSQL
★ 8A server for interacting with Microsoft SQL Server databases using the node-mssql library.
MySQL MCP Server
★ 8Provides access to a MySQL database, allowing agents to execute SQL queries.
Vertica MCP Server
★ 8Provides read-only access to Vertica databases.
schemabrain
★ 8A read-only trust layer between AI agents and your SQL database — the agent never writes SQL, PII is refused before the query runs, and every call lands in a tamper-evident audit log.
YugabyteDB MCP Server
★ 8Allows LLMs to directly interact with a YugabyteDB database.
Microsoft Access Database
★ 8Allows AI to interact with Microsoft Access databases, supporting data import and export via CSV files.
Kusto MCP Server
★ 7An MCP server for Azure Data Explorer (Kusto) that enables AI assistants to interact with Kusto databases.
LanceDB
★ 7A vector database server for storing, searching, and managing vector embeddings.
MySQL MCP Server
★ 7Provides direct access to MySQL databases, allowing AI agents to execute SQL queries and manage database content.
Couchbase
★ 7Interact with Couchbase databases using natural language. Perform CRUD operations, query buckets, and execute N1QL queries.
MCP Microsoft SQL Server
★ 7An MCP server for integrating with Microsoft SQL Server databases.
qmcp Server
★ 7An MCP server for integrating with and querying q/kdb+ databases.
ClickHouse Cloud & On-Prem
★ 7A server for managing ClickHouse databases and ClickHouse Cloud services.
Redshift Utils MCP Server
★ 6Perform database actions on Amazon Redshift via its Data API.
ADO.NET MCP Server
★ 6A C# MCP server for interacting with databases via ADO.NET, compatible with Virtuoso.
MCP Vertica
★ 6A server for managing and querying Vertica databases, including connection, schema, and security management.
Redis
★ 6A server for interacting with Redis databases.
MySQL
★ 6Interact with and manage MySQL databases. Requires connection details configured via environment variables.
ORMCP
★ 6ORMCP provides a curated, object-oriented, MCP-compliant view of relational data in any JDBC-compliant database (e.g., PostgreSQL, MySQL, Oracle, SQL Server, DB2, SQLite) — improving reasoning clarity, reducing token usage, and establishing a clear governance boundary.