"Rich" matching MCP servers:

A comprehensive Model Context Protocol (MCP) server that provides access to the AlphaFold Protein Structure Database through a rich set of tools and resources for protein structure prediction analysis.

Provides AI coding agents with persistent memory by recording sessions and normalizing them into a searchable knowledge graph, then delivering relevant context at the start of the next session.

Provides AI coding assistants with persistent, context-rich memory of a codebase, including documentation and git history, enabling recall across sessions.

An MCP server that acts as an AI knowledge and skills hub, automatically discovering, indexing, and serving skill libraries to any MCP client with full-text search, rich metadata, and hot reload.

Provides structured access to a temporal knowledge platform for searching historical events and browsing a causal graph of over 2,000 years of history. It enables users to generate rich historical scenes, interact with period-appropriate characters, and run complex temporal simulations.

Enables management of Kanban-backed task checkpoint documents in Obsidian, supporting task creation, querying, checkpoint commits, and rich block storage via MCP tools.

An MCP server implementing memory solutions for data-rich applications using HippoRAG for efficient knowledge graph capabilities, enabling search across multiple sources including uploaded files.

Serves markdown instructions as tools to provide LLMs with team playbooks, coding standards, domain knowledge, and personal workflows through version-controlled files.