"Markdown MCP (Model Context Protocol) Server" matching MCP servers:

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

Provides structured, addressable access to a local markdown vault with heading-anchored fragments, BM25 search, and stable IDs for verifiable retrieval.

A generic Markdown vault MCP server with FTS5 full-text search, semantic vector search, frontmatter-aware indexing, incremental reindexing, and non-markdown attachment support that exposes search, read, write, and edit tools.

Agent-controlled markdown files with frontmatter-based permissions, enabling read, append, or edit access for AI agents.

Enables AI clients to read and write to a user-owned markdown bucket via S3-compatible storage, providing a persistent shared context layer across different AI tools.

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

MCP server that converts PDF, video, web, and audio inputs into structured Markdown notes with support for checkpointing, batch processing, and Obsidian integration.

Enables managing and searching markdown notes with semantic search, question answering, and note generation, and provides an MCP server for GitHub Copilot integration.

Enables LLMs to access a user's personal writing context—voice, style, opinions, expertise, projects, and communication patterns—via curated markdown files, helping the LLM match the user's voice when generating written content.

Converts XMind mind map files into structured Markdown documents, preserving hierarchy and optionally including metadata.

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 coding agents to search and read local Markdown knowledge bases generated by Agent Docs for Markdown, across single or multiple workspaces, including link/backlink discovery and index status checks.

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

Enables AI assistants to search, read, and navigate a folder of Markdown notes as a knowledge base, with full-text search, backlinks, tags, metadata, and note resources for conversation attachment.

Enables Claude to pull curated context from self-hosted Markdown files via a remote MCP connector, with an append-only journal for agent notes manually promoted by the owner.

Enables agents to import selected conversation archives, search and edit an Obsidian-compatible Markdown memory wiki, and read/write shared context across AI clients through MCP.

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.

Persistent memory for AI agents enabling saving, searching, and managing knowledge across sessions with local markdown files.

Enables AI agents to read, search, create, and append Markdown notes from a local vault (e.g., Obsidian) via MCP, allowing natural-language note management through compatible clients.

Private tooling to stage ChatGPT conversations into reviewable Homebase markdown and Notion drafts with redaction and classification.

This MCP server lets any compatible AI assistant read, extend and connect the matters in a person's life — plans, trips, people and places — from a repository that belongs to the user, so a new assistant picks up where another left off. It keeps the user's words verbatim, records every change, and stores the repository as a plain file on the user's own computer.

Stores personal context as markdown files and exposes them via MCP for AI assistants to retrieve user preferences, skills, and background.

Enables MCP clients to query project-scoped Graphify graphs, search, read, and write Obsidian Markdown notes, and recall or store persistent ICM memories over authenticated private HTTPS. It serializes access per project and supports slim and standard Docker deployments without embeddings or extra memory services.

Parses an Obsidian vault and exposes structured context (notes, blocks, tasks, headings) through MCP tools, enabling AI clients to query and reason over local markdown notes.

An open-source memory layer that provides persistent project context and architectural history for AI development tools across multiple platforms and sessions. It enables AI assistants to maintain a shared understanding of codebases while integrating directly with services like Notion for documentation management.

An MCP server for saving, managing, and enhancing context with pre-processing strategies like clarification, analysis, and search optimization.

Enables MCP-compatible clients to query an Obsidian vault through a local, read-only broker, returning compact, cited context packs with source paths and heading anchors while enforcing a fail-closed sensitivity boundary.

A simple notes MCP server that enables creating, listing, and summarizing text notes via resources, tools, and prompts.

Lets AI agents retrieve source-linked passages from a local folder of Markdown notes or an Obsidian vault, optionally following the explicit links between notes, and can also fetch passages from pinned public GitHub files you configure. It returns bounded evidence packets with original text, file paths and hashes so agents can answer from your material rather than generating content themselves.