"Searching PubMed references and formatting them in Markdown" matching MCP servers:

Enables AI to search, retrieve, list notes, and get backlinks from a published Markdown vault (Obsidian) via GitHub Pages.

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

Headless semantic MCP server for Obsidian, Logseq, Dendron, Foam, and any markdown folder. Features built-in hybrid semantic search, surgical AST editing, template scaffolding, zero-config local embeddings, and workflow tracking.

Python MCP server for programmatic access to markdown-based knowledge vaults, enabling AI assistants to browse, read, search, update, and manage notes, tasks, and projects.

Enables AI assistants to query and interact with a graph database of markdown notes, extracting entities like wikilinks, mentions, and hashtags.

Enables querying Markdown files in knowledge bases (like Obsidian vaults) by front matter metadata, filtering notes by tags, recency, and folders to surface relevant content based on created/updated dates.

Enables AI agents to maintain a structured Markdown or Obsidian memory vault with tools for reading, writing, searching, and organizing notes.

Imagine you could hand Claude a filing cabinet of your documents and say "remember all of this." Later you just ask questions, and Claude answers from what it remembers — citing which document each fact came from. That's Memorised them All. It's a small add-on (an MCP server) for Claude Desktop and Claude Code that: Reads your files — PDFs, Word/Excel/PowerPoint, web pages, images (with OCR), ev

Enables AI agents to persist all generated deliverables as structured Markdown in a project's /.aiartefact directory, with automatic frontmatter, metadata indexing, and full-text search.

Local-first memory server for AI coding agents that stores work sessions, tasks, and durable memories in Markdown files, exposed through MCP tools for session management and memory retrieval.

Provides hybrid search over local markdown knowledge bases using BM25 keyword search and vector semantic search. Enables indexing, querying, and retrieving markdown documentation with dual-mode support for local and remote agents.

Provides a hierarchical memory management system using Markdown files. Enables creating, reading, linking, splitting, and archiving memory files with bidirectional wikilinks, keyword+graph search, and optimistic concurrency control.

Enables local MCP clients to list, read, write, and search notes in an Obsidian vault via an HTTP server running inside Obsidian.

Local markdown notes for any MCP client: ranked + semantic search, tags, todos, a wiki-link knowledge graph, daily notes, templates, and slash-command workflows. Pure-JS, local, no API keys.

Local-first MCP server that extracts structured knowledge from markdown notes into SQLite with full-text search, enabling AI coding tools to retrieve relevant context offline at zero cost.

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

Enables AI agents to store and retrieve project context, bugs, decisions, and session logs by reading and appending markdown files in a local Obsidian vault, without requiring any cloud services.

Enables Claude and ChatGPT to share a single study-progress database for interview prep, coursework, and spaced repetition, with per-user data isolation and server-side SM-2 scheduling for due reviews and study plans.

TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.

Enables indexing local documents (PDF, Markdown, text, code) into a knowledge base and querying them via semantic search using local embeddings, all running privately on your machine.