by aaronsb · MCP Server · ★ 454
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Semantic Notes Vault MCP 📦 Available in the Obsidian Community Plugin directory → Give AI semantic agency over your knowledge graph This plugin connects your Obsidian vault to AI assistants through MCP (Model Context Protocol), giving them the ability to understand and navigate your notes as a connected knowledge graph, not just isolated files. Through semantic hints and graph traversal, AI gains the agency to explore concepts, follow connections, and synthesize information across your entire vault. MCP (Model Context Protocol) is the open standard that lets AI assistants interact with external tools and data sources. This plugin works with any MCP-compatible client including: Claude Desktop (Anthropic) Claude Code/Continue.dev (VS Code) Any platform that supports local MCP servers Quick Start Prerequisites: an MCP-compatible AI client like Claude Desktop, Claude Code, or Continue.dev. ## 📦 ──drag──▶ �
| Stars | 454 |
| Forks | 51 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 74.0471962268667/100 |
| Open Issues | 13 |
| Last Updated | 2026-08-08 |
| Created | 2025-06-27 |
| Platforms | claude-code, mcp, node |
| Est. Tokens | ~16k |
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obsidian-mcp-plugin is High-performance Model Context Protocol (MCP) server for Obsidian that provides AI tools with direct vault access through semantic operations and HTTP transport.. It is categorized as a MCP Server with 454 GitHub stars.
obsidian-mcp-plugin is primarily written in TypeScript. It covers topics such as ai, claude, knowledge-graph.
You can find installation instructions and usage details in the obsidian-mcp-plugin GitHub repository at github.com/aaronsb/obsidian-mcp-plugin. The project has 454 stars and 51 forks, indicating an active community.
obsidian-mcp-plugin is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to obsidian-mcp-plugin on Agent Skills Hub include mcp-memory-service, omega-memory, pdf-mcp. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.