--- title: "obsidian-llm-wiki-local vs mcp-local-rag" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kytmanov-obsidian-llm-wiki-local-vs-shinpr-mcp-local-rag" tools: ["kytmanov-obsidian-llm-wiki-local", "shinpr-mcp-local-rag"] --- # obsidian-llm-wiki-local vs mcp-local-rag *GraphCanon updated Sep 20, 2026* ## Verdict Pick obsidian-llm-wiki-local if local-first AI wiki for auto-linking Markdown notes with LLMs in Obsidian, designed to maintain user privacy; pick mcp-local-rag if mcp-local-rag is designed for developers who prioritize privacy and ease of setup when performing semantic and keyword searches on local codebases and technical documents through MCP or CLI integration. [obsidian-llm-wiki-local](https://github.com/kytmanov/obsidian-llm-wiki-local) reports 827 GitHub stars, 127 forks, and 2 open issues, last pushed May 26, 2026. [mcp-local-rag](https://github.com/shinpr/mcp-local-rag) has 400 stars, 74 forks, and 2 open issues, last pushed Sep 20, 2026. Figures are from public GitHub metadata via [obsidian-llm-wiki-local's repository](https://github.com/kytmanov/obsidian-llm-wiki-local) and [mcp-local-rag's repository](https://github.com/shinpr/mcp-local-rag). | | [obsidian-llm-wiki-local](/tools/kytmanov-obsidian-llm-wiki-local.md) | [mcp-local-rag](/tools/shinpr-mcp-local-rag.md) | | --- | --- | --- | | Tagline | Local-first AI wiki that integrates Markdown notes with LLMs for auto-linking concepts and personal knowledge management. | Local-first RAG server for developers with semantic and keyword search capabilities. | | Stars | 827 | 400 | | Forks | 127 | 74 | | Open issues | 2 | 2 | | Language | Python | TypeScript | | Adopt for | Local-first AI wiki for auto-linking Markdown notes with LLMs in Obsidian, designed to maintain user privacy. | mcp-local-rag is designed for developers who prioritize privacy and ease of setup when performing semantic and keyword searches on local codebases and technical documents through MCP or CLI integration. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Data & Retrieval, Developer Tools | Data & Retrieval, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [obsidian-llm-wiki-local](/tools/kytmanov-obsidian-llm-wiki-local.md) | [mcp-local-rag](/tools/shinpr-mcp-local-rag.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 117d | 0d | | Stars delta | +28 (30d) | +48 (30d) | | Open issues delta | 0 (30d) | -2 (30d) | | Full report | [trust report](/tools/kytmanov-obsidian-llm-wiki-local/trust.md) | [trust report](/tools/shinpr-mcp-local-rag/trust.md) | ## Decision facts: obsidian-llm-wiki-local - **Adopt for:** Local-first AI wiki for auto-linking Markdown notes with LLMs in Obsidian, designed to maintain user privacy. ## Decision facts: mcp-local-rag - **Adopt for:** mcp-local-rag is designed for developers who prioritize privacy and ease of setup when performing semantic and keyword searches on local codebases and technical documents through MCP or CLI integration. ## Choose when ### Choose obsidian-llm-wiki-local if… - obsidian-llm-wiki-local is primarily Python; mcp-local-rag is TypeScript. - Tags unique to obsidian-llm-wiki-local: git-based-wiki, karpathy, knowledge-base, llm-knowledge-base. - When you require a self-contained wiki solution that uses local Large Language Models (LLMs) and keeps all data private. ### Choose mcp-local-rag if… - mcp-local-rag is primarily TypeScript; obsidian-llm-wiki-local is Python. - Tags unique to mcp-local-rag: agent-skills, hybrid-search, local-first, privacy-first. - mcp-local-rag ships an MCP server manifest. - When you need to perform both semantic and keyword-based search operations within a local, privacy-focused environment tailored specifically for handling codebases and technical documentation. ## When NOT to use obsidian-llm-wiki-local - If you do not have a preference for using local LLMs over cloud-based solutions that might offer more powerful models. - When you are willing to share your data with external services for potentially better integration features or enhanced AI capabilities. ## When NOT to use mcp-local-rag - When you do not require a privacy-first approach and are willing to rely on cloud-based solutions that might offer more extensive feature sets beyond just keyword and semantic searches. - If your use case involves scaling search capabilities across multiple remote databases or servers, as mcp-local-rag is best suited for local data only. ## Common questions ### What is the difference between obsidian-llm-wiki-local and mcp-local-rag? obsidian-llm-wiki-local: Local-first AI wiki that integrates Markdown notes with LLMs for auto-linking concepts and personal knowledge management.. mcp-local-rag: Local-first RAG server for developers with semantic and keyword search capabilities.. See the comparison table for live GitHub stats and shared categories. ### When should I choose obsidian-llm-wiki-local over mcp-local-rag? Choose obsidian-llm-wiki-local over mcp-local-rag when obsidian-llm-wiki-local is primarily Python; mcp-local-rag is TypeScript; Tags unique to obsidian-llm-wiki-local: git-based-wiki, karpathy, knowledge-base, llm-knowledge-base; When you require a self-contained wiki solution that uses local Large Language Models (LLMs) and keeps all data private. ### When should I choose mcp-local-rag over obsidian-llm-wiki-local? Choose mcp-local-rag over obsidian-llm-wiki-local when mcp-local-rag is primarily TypeScript; obsidian-llm-wiki-local is Python; Tags unique to mcp-local-rag: agent-skills, hybrid-search, local-first, privacy-first; mcp-local-rag ships an MCP server manifest; When you need to perform both semantic and keyword-based search operations within a local, privacy-focused environment tailored specifically for handling codebases and technical documentation. ### When should I avoid obsidian-llm-wiki-local? If you do not have a preference for using local LLMs over cloud-based solutions that might offer more powerful models. When you are willing to share your data with external services for potentially better integration features or enhanced AI capabilities. ### When should I avoid mcp-local-rag? When you do not require a privacy-first approach and are willing to rely on cloud-based solutions that might offer more extensive feature sets beyond just keyword and semantic searches. If your use case involves scaling search capabilities across multiple remote databases or servers, as mcp-local-rag is best suited for local data only. ### Is obsidian-llm-wiki-local or mcp-local-rag more popular on GitHub? obsidian-llm-wiki-local has more GitHub stars (827 vs 400). Stars measure visibility, not whether either tool fits your constraints. ### Are obsidian-llm-wiki-local and mcp-local-rag open source? Yes - both are open-source projects on GitHub (obsidian-llm-wiki-local: MIT, mcp-local-rag: MIT). ### Where can I find alternatives to obsidian-llm-wiki-local or mcp-local-rag? GraphCanon lists graph-backed alternatives at [obsidian-llm-wiki-local alternatives](/tools/kytmanov-obsidian-llm-wiki-local/alternatives) and [mcp-local-rag alternatives](/tools/shinpr-mcp-local-rag/alternatives) ([obsidian-llm-wiki-local markdown twin](/tools/kytmanov-obsidian-llm-wiki-local/alternatives.md), [mcp-local-rag markdown twin](/tools/shinpr-mcp-local-rag/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/kytmanov-obsidian-llm-wiki-local-vs-shinpr-mcp-local-rag.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, obsidian-llm-wiki-local or mcp-local-rag? obsidian-llm-wiki-local: Slowing. mcp-local-rag: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for obsidian-llm-wiki-local and mcp-local-rag? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [obsidian-llm-wiki-local trust report](/tools/kytmanov-obsidian-llm-wiki-local/trust); [mcp-local-rag trust report](/tools/shinpr-mcp-local-rag/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kytmanov-obsidian-llm-wiki-local`](/api/graphcanon/graph?tool=kytmanov-obsidian-llm-wiki-local) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_