"Postgres" matching MCP servers:

Enables AI agents to execute SQL queries and introspect PostgreSQL schemas, tables, and indexes with read-only safety by default. Supports optional write operations and works with Claude, LangChain, and other agents via stdio or HTTP transports.

An open-source MCP server that provides AI agents with advanced PostgreSQL capabilities including index tuning, query plan optimization, and comprehensive database health analysis. It supports safe SQL execution through configurable access modes and offers both stdio and SSE transport options for various development environments.

A PostgreSQL MCP server that automatically detects and obfuscates personally identifiable information (PII) in query results using column-name heuristics and NLP analysis. It enables AI agents to interact securely with databases by masking sensitive data by default while allowing selective unmasking under user control.

Acts as a secure bridge connecting PostgreSQL databases to AI models, enabling natural language querying, schema analysis, and controlled write operations with multi-layer security.

Enables SQL queries against PostgreSQL databases through MCP-compatible clients and includes a natural language agent for forming SQL queries from natural language.

Enables natural language queries to a Neo4j knowledge graph built from PostgreSQL data, integrating with Claude Desktop and REST API.

Enables AI agents to execute any SQL command (including DDL/DML) on a PostgreSQL database with zero restrictions, allowing full database control and dynamic database switching.

This is an MCP server for PostgREST. It allows LLMs perform database queries and operations on Postgres databases via PostgREST. This server works with both Supabase projects (which use PostgREST) and standalone PostgREST servers.

MCP server exposing memory search, index, and stats tools for agents, with honesty guards to prevent re-litigation of settled decisions.

A governed SQL gateway that exposes typed tools to AI agents, compiling safe read-only queries from a semantic layer while blocking PII before execution, supporting SQL Server, Postgres, and SQLite.

An MCP server that incrementally indexes repositories and documents into a Postgres + pgvector store using CocoIndex, and exposes semantic search over them.

An agent-neutral MCP server providing SQLite key/value storage, Postgres knowledge base, and Kart task queue functionality. Features SAP/1.0 authorization on every tool call for secure multi-application access.

A domain-specific MCP server that provides optimized API access to the RAGmonsters fictional monster dataset, enabling more efficient and secure interactions compared to generic SQL queries.

Hardware-accelerated codebase mapping that indexes Git repositories into Postgres/pgvector and serves code search, relationships, and static analysis results via a stdio MCP server.

AI-native open-source backend-as-a-service. Manage Postgres with RLS, auth, file storage, serverless TypeScript functions, durable objects, realtime, KV, AI gateway, and RAG via MCP, either HTTP at /mcp on a self-hosted instance or stdio with npx @butterbase/mcp.

This read-only MCP Server allows you to connect to PostgreSQL data from Claude Desktop through CData JDBC Drivers. For full CRUD support, check out the first managed MCP platform: CData Connect AI (https://www.cdata.com/ai/).

Local-first MCP server for long-term memory of dev sessions. It indexes session metadata with embeddings in Postgres/pgvector, enables semantic search over past sessions, and resolves only relevant session files for context.

Enables AI agents to query, explore, and analyze PostgreSQL databases through the Model Context Protocol. It provides robust security features including read-only mode, schema restrictions, and query timeouts for safe data interaction.

Provides AI agents an auditable memory layer with provable deletion via signed certificates, a tamper-evident hash-chained audit trail, and bi-temporal time-travel recall over SQLite or Postgres.

dolores is an MCP server that gives AI agents persistent memory using Postgres and pgvector, retrieving only relevant context to minimize token usage.