by takeshy · MCP Server · ★ 50
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
Local LLM Hub for Obsidian Your company's security policy blocks cloud APIs. But you refuse to give up AI-powered note automation. Local LLM Hub brings the full power of Gemini Helper's workflow automation, RAG, MCP integration, and agent skills to a completely local environment. Ollama, LM Studio, vLLM, or AnythingLLM — your data never leaves your machine. Why Local? Every byte stays on your machine. No API keys sent to the cloud. No vault contents uploaded anywhere. This isn't a privacy "option" — it's the architecture. If you use Gemini Helper at home but need something for work — this is it. Same workflow engine, same UX, zero cloud dependency. Workflow Automation — The Core Feature Describe what you want in plain language. The AI builds the workflow. No YAML knowledge required. Create Workflows & Skills with AI Open the Workflow / s
| Stars | 50 |
| Forks | 4 |
| Language | TypeScript |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.3475729441182/100 |
| Last Updated | 2026-07-01 |
| Created | 2026-03-06 |
| Platforms | mcp, node |
| Est. Tokens | ~17k |
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obsidian-local-llm-hub is All-in-one local AI hub for Obsidian — LLM chat with vault tools, MCP servers, RAG, workflow automation, encryption, and edit history. Fully private, no cloud required.. It is categorized as a MCP Server with 50 GitHub stars.
obsidian-local-llm-hub is primarily written in TypeScript. It covers topics such as local-llm, memo-app, obsidian-plugin.
You can find installation instructions and usage details in the obsidian-local-llm-hub GitHub repository at github.com/takeshy/obsidian-local-llm-hub. The project has 50 stars and 4 forks, indicating an active community.
obsidian-local-llm-hub is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to obsidian-local-llm-hub on Agent Skills Hub include agentic-signal, askimo, InferrLM. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.