"Postgres" matching MCP servers:

Zero-config PostgreSQL MCP server with auto-provisioning. Drop-in replacement for @modelcontextprotocol/server-postgres — no DATABASE_URL needed.

Provides Claude Code read-only access to PostgreSQL for relational queries, schema inspection, EXPLAIN plans, pgvector similarity searches, and Apache AGE graph traversals.

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.

Enables secure, AI-driven PostgreSQL database administration, observability, and querying with support for extensions like PostGIS and pgvector, connection pooling, and advanced tool filtering.

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

Semantic memory for AI builders: capture the tacit engineering know-how that never reaches your docs, recall it the moment it applies. Built in Rust on Postgres and pgvector.

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

It connects an agent to a PostgreSQL database so it can inspect schemas, run validated reads and writes, resolve fuzzy names via trigram search, and perform or store pgvector embedding searches. Vector and hybrid search operate through an OpenAI-compatible embeddings endpoint, letting agents query by text without handling embedding arrays.

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.

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.

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

Enables semantic and keyword search across locally indexed PDF shelves—device manuals, meeting minutes, and scientific papers—with date, device, and author filters, returning structured citations and neighbouring passage context for a speech assistant. It also exposes shelf and document metadata, plus a reindex signal, over streamable HTTP backed by Postgres with pgvector.

Agentic RAG Knowledge Assistant is a secure, tenant-isolated MCP server built with FastAPI, PostgreSQL, and pgvector that enables document ingestion, semantic retrieval, and vector search over PDF, DOCX, and text files through authenticated MCP tools.

Provides MCP agents with persistent memory operations (store, recall, forget, consolidate, list) backed by Redis, Postgres, and pgvector, including semantic search and background consolidation.

A self-hostable MCP server that provides permanent memory for AI agents using Postgres + pgvector for semantic search and Markdown file sync.

Enables semantic search and management of Zotero reference libraries using PostgreSQL with pg-vector and OpenAI/Ollama embeddings. Provides AI-powered search, full-text extraction, metadata access, annotations, notes, tags, and collections management.

User-owned shared memory for AI agents, providing a persistent, curated knowledge layer with hybrid search and cross-agent coordination via Postgres + pgvector.

Enables an AI agent to recall past approvals, edits and rejections that are similar to the task at hand before drafting, and to record each new decision along with the human's reason. Memory lives in a local Postgres (PGlite + pgvector) store, so corrections carry across sessions without hosting anything.

A self-hosted, multi-context memory server that enables AI agents to search and retrieve information from local documents and crawled websites via MCP tools. It runs fully offline using Postgres and Ollama to provide secure, private knowledge management and retrieval-augmented generation.

Unifies LAN agent memory (Postgres + pgvector + Ollama) with an Obsidian vault adapter, exposing tools for semantic recall, knowledge base search/write, and memory management.