"A guide to finding data in public databases" matching MCP servers:

An MCP server that transforms books into agent-callable skill packages, enabling AI agents to use books as guides for evidence, procedures, and tutoring.

Persistent memory and pattern learning for AI coding assistants via MCP.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

A semantic-memory MCP server that stores text 'memories' with provenance and enables recall by meaning (vector search), keyword (FTS5), or structured filters.

Provides an intelligent, graph-based memory system for LLM agents using the Zettelkasten principle, enabling automatic note construction, semantic linking, memory evolution, and autonomous graph maintenance with background optimization processes.

Enables personal knowledge management through Claude Desktop, allowing users to capture thoughts, connect ideas, and reflect on thinking changes via natural conversation.

Provides a single-writer MCP server for a governance-grade knowledge base of markdown documents with version control and query capabilities.

Turn Obsidian notes into agent-ready context, preview-only plans, and safe repo handoffs.

Metis — an open-source (AGPL-3.0), local-first MCP server / research companion. It answers from the user's own indexed PDF library with page-level citations (and flags what it can't find rather than inventing), keeps all data on the user's machine, and routes requests to 34 specialist agents.

Enables agents to optimize context-window attention by reordering retrieved documents so critical evidence lands at prompt boundaries, mitigating lost-in-the-middle degradation. It combines BM25 lexical scoring, dense vector similarity, reciprocal rank fusion, knowledge-graph expansion, and recency-decay memory caching, exposed as a zero-dependency MCP stdio server.

Enables agents to run hybrid retrieval, reciprocal rank fusion, knowledge graph expansion, semantic caching, and context reordering so critical evidence is placed at prompt boundaries to reduce lost-in-the-middle degradation.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Provides AI clients with a governed, searchable catalog of go-to-market context, including ownership, measurement, lineage, runbooks, and bulk-change templates. Optionally integrates with the UTM Builder for governed UTM reference data, preview, and issuance.

Enables AI agents to maintain persistent, searchable two-layer memory with 37 tools, hybrid search, knowledge graphs, and enterprise features like authentication and backups.

Project management and session memory for AI agents that provides 13 tools for tracking projects, tasks, and context during AI coding sessions.

Look up countries, timezones, periodic table elements, physical constants, units, HTTP status codes, and MIME types via MCP. STDIO or Streamable HTTP.

Connects Claude and ChatGPT to a marketplace of AI specialist packages, letting assistants discover and purchase on-chain licenses, activate them, then run each package's method step by step. It also exposes knowledge-base search, templates, persistent memory, tool execution, and deliverable submission with sandbox verification.

Enables querying PDF documents using natural language with grounded answers and source citations via a local RAG pipeline.