"Communicating with EHR systems like Epic using FHIR API" matching MCP servers:

Enables Claude to write in your personal style by learning from your local documents. It provides statistical style context for natural language rewriting, all without any data leaving your machine.

Enables AI harnesses to maintain a persistent memory layer backed by a local SQLite file, providing MCP tools to add, search, deprecate, and synchronize facts without deleting history.

Unofficial Notion MCP server built on Notion's private API (token_v2 cookie). Gives LLM agents full read/write access to the entire workspace — no integration token and no per-page sharing.

MCP server exposing eight esoteric calculation systems (Western/Vedic astrology, Human Design, Gene Keys, and more) through 14 tools, with deterministic profiles, partial success, and OAuth integration.

Enables managing Zotero reference libraries with full CRUD operations, collections, notes, annotations, and attachments via the Zotero API.

Built-in MCP server that gives AI agents direct access to an Obsidian vault for reading, writing, searching notes, and executing commands.

AI assistant integration with Logseq knowledge graph: 21 tools to read, write, query, and search notes, enabling seamless interaction with your notes.

Provides human-like memory dynamics for AI assistants where memories naturally fade over time unless reinforced through use, mimicking the Ebbinghaus forgetting curve. Enables automatic saving, searching, and management of contextual information with temporal decay algorithms.

Memory bank with Server as SSH support for central knowledge base

MCP server for alive-analysis. Query, search, and retrieve structured analysis history written with the ALIVE loop (Ask→Look→Investigate→Voice→Evolve), plus dashboard JSON export.

Facilitates knowledge graph representation with semantic search using Qdrant, supporting OpenAI embeddings for semantic similarity and robust HTTPS integration with file-based graph persistence.

Connects Bear Notes to AI assistants using semantic search and RAG (Retrieval-Augmented Generation), allowing AI systems to access and understand your personal knowledge base through meaningful search rather than just keyword matching.

MemOS (Memory Operating System) is a memory management operating system designed for AI applications. Its goal is: to enable your AI system to have long-term memory like a human, not only remembering what users have said but also actively invoking, updating, and scheduling these memories.

Enables querying and analyzing Danish legislation, including search, citation validation, currency checks, and EU law integration, directly from AI assistants.

A Model Context Protocol server that enables AI agents to query a Graphiti knowledge graph and pgvector document store for evidence-backed responses via hybrid search and RAG.

A server that enables AI agents to perform sophisticated knowledge discovery and analysis across Obsidian vaults through the Local REST API plugin, supporting complex multi-step workflows with advanced filtering and full content retrieval.

Japan Operations OS for AI agents — 14 knowledge domains covering regulations, protocols, calendar, travel, food culture, language, disaster safety, daily life, and persistent memory. 31 MCP tools via REST + Streamable HTTP.

Integrates with Red Hat APIs to enable searching Knowledge Centered Support (KCS) solutions, retrieving solution details, searching support cases, and obtaining case details through LLM applications.

Enhances user interaction through a persistent memory system that remembers information across chats and learns from past errors by utilizing a local knowledge graph and lesson management.

Enables Claude Code to query codebase knowledge graphs directly, reducing token usage 5x–71x by reading a compact graph.json instead of raw files.