"postgres" matching MCP servers:

Governed PostgreSQL DBA operations — slow-query, bloat, and blocking-lock RCA, index management, vacuum/analyze, and replication lag, with unbypassable audit logging (MCP + CLI), budget/runaway guards, dry-run, and undo/rollback.

MCP server with 14 tools for PostgreSQL database operations. Query databases, explore schemas, analyze tables, with SQL injection prevention and read-only mode by default.

A drop-in Model Context Protocol (MCP) server that lets an AI agent query PostgreSQL — read-only, enforced at the database level, with real SQL validation, timeouts, cost limits, OAuth 2.1, and an audit trail.

Enables AI assistants to query PostgreSQL, inspect schemas, and explain queries, designed for local and development databases with read-only safety by default.

Query PostgreSQL and inspect schemas over MCP. Connects to local, Docker, RDS, Neon, Supabase, or a database behind an SSH bastion.

A production-grade Model Context Protocol server for PostgreSQL. Lets AI agents safely inspect, query, operate, and tune a Postgres database — over 100 tools spanning catalog introspection, query intelligence, natural-language SQL, structural diffs, hybrid search, graph queries, data movement, live ops, and more.

Reviewed Postgres and MySQL business actions for MCP agents, without exposing raw execute_sql.

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

Explains known developer errors offline and deterministically (CORS, ESM/CommonJS, npm ERESOLVE, Next.js builds, Postgres connection and DATABASE_URL errors). One tool, explain_error; no LLM, no network.

Access control for text-to-SQL agents. Before the model sees the schema, schemagate keeps only the tables and columns the caller may read, picks the few a question needs, and refuses hidden ones at query time. Postgres, Oracle, MySQL, SQL Server, SQLite. Quantum-safe signed audit log. Try it in your browser: https://ashishsinha1602.github.io/schemagate/

Read-only, PII-masked MCP server for querying data federated through DuckDB — list sources/tables, inspect schemas, and run SQL across Postgres, MySQL, SQLite, Snowflake, BigQuery, Excel, and files, governed per source/table/column by a charter.yaml contract. Snowflake, BigQuery, Excel, and files, governed per source/table/column by a charter.yaml contract.

Answers natural-language questions against Postgres, Oracle, Snowflake, Databricks, DuckDB and SQLite via db_read(question) and get_schema(), each separately grantable. The model only proposes SQL — shape, access, dialect and query plan are checked deterministically before any rows are read, and the server refuses rather than returning an unverified answer.

Analytical memory for AI agents: a real Postgres your agent connects to over MCP and queries in plain English — GROUP BY, JOIN, aggregate over what it remembered, not just top-k vector recall.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Self-hostable uptime monitoring with an MCP server for managing monitors, incidents, and status pages. Runs with Docker and Postgres, with Streamable HTTP, OAuth, and API key authentication.

Agent memory for facts that change. When a user corrects something, Recall replaces the old fact, tells the agent what it replaced, and keeps the old value in a history. Ask what was believed on any date, see every change to a fact, or diff two dates. Runs locally on polign_db, Postgres with pgvector, MongoDB, or Qdrant. Apache 2.0.

Blocks unsafe PostgreSQL migrations before an AI agent writes or runs them. check_before_apply returns a pass/fail gate; reads the real Postgres parser, classifies the lock each statement takes, checks 112 safety rules. Runs offline, no database required.

Self-hosted shared memory for AI coding tools: any MCP client can save, search (Postgres + pgvector) and recall project knowledge. Includes a web UI and Docker Compose setup.

Enables AI agents to run read-only Postgres bloat diagnostics, returning per-table and per-index verdicts with supporting evidence, actionable fixes, and timeline history. It also identifies blocking sessions and can take a one-shot throwaway snapshot for live production diagnosis without touching stored timeline data.

Zero-config data quality monitoring as MCP tools. Profiles a warehouse (Postgres, BigQuery, Snowflake, MySQL, DuckDB), detects anomalies, and gates CI — read-only with the connection resolved server-side, never via the model.