"Managing a PostgreSQL Database" matching MCP servers:

Enables persistent, auditable business operations state by storing knowledge, evidence, decisions, tasks, execution receipts, and review results in a local SQLite database, so different sessions can continue the same project.

Provides versioned, structured memory for AI agents, allowing them to store facts, detect conflicts, and track knowledge history via a hosted SaaS platform. It enables efficient hierarchical information retrieval and semantic search while keeping token usage constant as memory scales.

Read-only MCP access to the p-e relay store: an append-only corpus of provenance-bearing coordination records, with tools to fetch a record by id, list records and replies, and check existence. This image serves a snapshot frozen at build time; append_relay is listed but refused, and deposits to the live store require an HMAC-signed request.

Provides tools for managing project knowledge graphs, enabling structured representation of projects, tasks, milestones, resources, and team members.

Author rules from policy docs, then decide: a Rete engine gives the verdict, an LLM explains why.

An MCP server that provides AI agents with a persistent, PostgreSQL-backed virtual filesystem, supporting session-isolated file operations, cross-session shared stores, and glob/grep search.

Local-first shared memory and coordination layer for AI coding agents, with repository evidence, reservations, handoffs, code graph context, and dashboard review backed by PostgreSQL/pgvector.

A personal notes MCP server that allows AI assistants to create, search, edit, and manage notes stored in a local SQLite database.

A codebase-memory MCP server for AI coding agents with hybrid semantic+BM25 code search, structural outlines, a work journal, and gaze-and-think deep reasoning over a local LanceDB database.

A Model Context Protocol server that enables AI agents to interact with a local Logseq instance, allowing operations like creating pages, managing blocks, and searching across a knowledge graph.

A self-contained, in-memory graph database for AI Agents. Provides semantic code understanding through the Model Context Protocol (MCP).

Self-hosted MCP server for Obsidian with semantic + full-text search over PostgreSQL/pgvector, wikilink graph traversal, atomic note CRUD, OAuth 2.0, and a self-describing vault guide.

A static, read-only MCP server that exposes a database knowledge base (schema, relationships, workflows, and reasoning patterns) so Claude Code / Copilot can reason about a database without a live connection.

A personal memory MCP server that ingests AI agent conversation logs from multiple platforms into a searchable PostgreSQL+pgvector database, enabling cross-session recall of past reasoning and decisions.

Provides a read-only interface to audit and continue coding agent sessions by extracting plans, intents, and edit authorship from history across multiple agents (Claude, Codex, OpenCode, Antigravity, Pi) via MCP, CLI, and Python SDK.

A privacy-first memory layer for AI that securely bridges local knowledge with AI assistants through MCP tools, with intelligent redaction and local vector database.

Provides a hybrid memory architecture with a thin SQLite index and Markdown cold storage, enabling AI agents to write, query, link, and rebuild long-term memories via MCP tools, model-agnostic and zero third-party dependencies.

A provider-neutral MCP server that provides tools for managing skills, agents, references, and artifact memory in a local workspace.

Analyzes GitLab group projects to extract purpose, I/O, dependencies, and database tables, serving this knowledge via MCP tools and a read-only HTML visualization.

A persistent, project-scoped memory layer for AI agents, supporting hybrid retrieval (vector, keyword, and tag matching) and sharing across different MCP clients like Claude Code, Qoder, or Cursor.