Obsidian MCP Server

Created By
cyanheadsa year ago
Model Context Protocol (MCP) server designed for LLMs to interact with Obsidian vaults. Provides secure, token-aware tools for seamless knowledge base management through a standardized interface.
Overview

What is Obsidian MCP Server?

Obsidian MCP Server is a Model Context Protocol (MCP) server designed for large language models (LLMs) to interact with Obsidian vaults, enabling seamless knowledge base management through a standardized interface.

How to use Obsidian MCP Server?

To use the Obsidian MCP Server, install Node.js, enable the Local REST API plugin in Obsidian, and clone the repository or install it via npm. Configure the MCP client settings with your API key and other parameters.

Key features of Obsidian MCP Server?

  • Atomic file and directory operations with validation.
  • Full-text search capabilities with advanced query support.
  • YAML frontmatter parsing and intelligent merging.
  • API key authentication with rate limiting and SSL options.

Use cases of Obsidian MCP Server?

  1. Managing and organizing notes in Obsidian vaults.
  2. Enabling AI assistants to perform complex searches and file operations.
  3. Facilitating secure and efficient knowledge management for research and data.

FAQ from Obsidian MCP Server?

  • What is the Model Context Protocol?

The Model Context Protocol (MCP) allows AI models to interact with external tools and resources through a standardized interface.

  • Is the server secure?

Yes, it features API key authentication, rate limiting, and SSL options for secure communication.

  • What are the system requirements?

You need Node.js and the Local REST API plugin enabled in Obsidian.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
cyanheads
Star
96
Language
TypeScript
License
Apache-2.0 license

Recommend Servers

View All
Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago