"postgres" matching MCP servers:

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

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.

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.

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 agents to perform spaced-repetition learning with FSRS scheduling, including adding cards, reviewing due cards, and grading recall, using a headless SQLite or Postgres backend.

Persistent memory for AI agents through the Model Context Protocol. MemStack provides tools to store, retrieve, summarize, prune, export, and manage memories using local files, SQLite, Postgres, Redis, or in-memory storage.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

Zaxy turns agent work into durable, auditable memory: a hash-chained Eventloom log as the source of truth, an embedded temporal knowledge graph for reasoning (local-first, no sidecar; Neo4j/Postgres optional), cited Memory Checkout for compact context, and MCP tools for model-facing retrieval, capture, and feedback.

Local-first, auditable memory for Codex, Claude Code, and MCP clients. It stores scoped user/project memory in SQLite or Postgres, serves read-only recall and inspection tools by default, and supports opt-in governed writeback with review and forget controls.

MCP server for lineage-gated AI agent memory on PostgreSQL + pgvector: a cached result is only returned if every sensitive column it was derived from is permitted for the caller’s role, enforced by Postgres row-level security rather than application code.

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.

Serves as a universal interface between AI Agents and AnalyticDB PostgreSQL databases, enabling metadata retrieval and SQL execution, with additional capabilities for knowledge graph and LLM memory management.

Enables MCP clients such as Claude Code, Codex, and Cursor to store, query, update, and share schema-less JSON records in a self-hosted Postgres-backed database across sessions.

Enables AI assistants to read, search, and write Markdown notes kept in Postgres, alongside a web app with a file tree, wikilinks, full-text search, and a graph. Supports OAuth or API-key connections, per-account vaults, and folders shared with other people read-only or read-write.

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.

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.

Enables AI agents to query a personal knowledge vault with hybrid search, entity relationships, user highlights, and vault statistics over a Supabase/Postgres schema.

Framework-agnostic MCP server for agent memory with Postgres + pgvector, enabling persistent memory, recall, and task management across sessions.