"How to use the git clone command" matching MCP servers:

This MCP server enables AI collaborators to read and write to a git-backed Obsidian vault with transactional integrity, ensuring every write is a validated, attributed commit pushed to the remote.

A dockerised, self-hostable host that runs an Obsidian vault headlessly and serves it to MCP clients, with pluggable sync (git first).

Long-term memory for Claude Desktop and Claude Code over plain markdown files on your machine. It returns nothing when the corpus has no answer, naming the terms that appear nowhere — no least-bad match dressed as an answer. And it verifies cited commit SHAs against git, so an agent can tell what actually shipped from what was only discussed and abandoned. Local; nothing is transmitted.

Enables coding agents to use an Obsidian vault as long-term memory, with search, reading, and writing of notes, plus automatic capture of learnings that are propagated to MOCs, daily notes, and the knowledge index with git commits.

Model-agnostic, agent-ready Obsidian MCP server with RBAC, SLSA provenance, and native search. 163 tools across 31 domains, multi-vault, pluggable embeddings.

Vulcanus turns a Git-versioned Markdown vault into structured project memory for coding agents. recall returns a project's capsule plus the read-next list, and warns when the capsule is older than the decisions beneath it. search ranks by layer, so the cheapest sufficient note surfaces first. Writes are scoped: update_capsule replaces one named section instead of rewriting the file, and `app

A stateless MCP server providing persistent, structured project memory for AI coding agents via a markdown folder. It allows agents to record decisions, plans, and notes, which are stored and synced with git.

Stores journal entries locally with semantic search using multilingual embeddings, and optionally syncs to a Git remote.

SeaMeet MCP connects Claude, Cursor, Codex, and other AI agents to SeaMeet meeting recordings, transcripts, AI summaries, screenshots, action items, webhooks, and desktop recording controls. Use it to search meeting memory, read synced cloud recordings, and automate meeting notes through the Model Context Protocol.

Enables agents to search, read, list, and amend a git-backed markdown knowledge base, automatically committing and publishing changes.

Exposes Obsidian-style Markdown vaults to MCP clients, enabling reading, writing, searching, and version-controlled editing of notes with automatic git snapshots and restore.

A Model Context Protocol server that turns your Joplin notebook into a tool an LLM can actually use — read, search, write, and organize notes, and pull OCR'd text straight out of your screenshots.

MCP server for structured daily work diary management, enabling entries, standup summaries, weekly reports, full-text search, and automatic git commits.

This MCP server enables AI assistants to perform calculations, fetch live weather, manage in-memory notes, access system info and note resources, and use reusable code review and summarization prompts.

Read-only MCP server that exposes Fathom meetings and transcripts as tools for use by skills in the TICKETS workspace.

MCP server for intelligent, use-adaptive Obsidian vault search. It uses Hebbian learning and graph centrality to rank files by usage and relevance.

Git-native Markdown content management CLI with a built-in MCP server. Lets AI clients (Claude, Cursor) search, read, write, and govern story/paper/note repositories, auto-generate READMEs, validate configs, and export EPUB or SFT training data.

Enables recording local Git push attempts via a fail-open pre-push hook and managing versioned daily drafts that can be reviewed, edited, rejected, and explicitly approved through MCP tools and an interactive UI.

A self-hosted MCP server that gives AI agents shared, long-term memory over a git-backed folder of markdown, enabling persistent knowledge search, read, and write without a database.

A local MCP server for low-token co-reading: import a book, split it into chapter-sized chunks, read it chunk by chunk, and keep notes so a session can resume without re-reading the whole book.