MCP server
Obsidian MCP server
A community MCP server that lets AI list, read, search, edit, append to and delete notes in an Obsidian vault through the Local REST API plugin.
- Community server
- Knowledge and memory
At a glance
- Maintained by
- Markus Pfundstein (community)
- Tools exposed
- 7 listed below
- Reviewed
- September 24, 2026
Why it matters
What it does and why it matters
Obsidian is a note-taking app built on plain markdown files, popular with people who keep personal knowledge bases. This community MCP server connects an assistant to a vault through Obsidian's Local REST API plugin. It can list files, read notes, search, patch content, append to notes and delete files.
For consultants, researchers and managers who think in notes, it lets an assistant find connections, summarize topics and file new ideas in the right place.
We did not find an official Obsidian MCP server, so this is the most widely used community option, by Markus Pfundstein. It needs the Local REST API plugin and its key. Because it can edit and delete notes, back up the vault and review changes, especially deletes.
Use cases
Best business use cases
Search notes
Topic summaries
Capture ideas
Find connections
Daily notes
Tools
Available tools
Tool names as published by the maintainer at review time. Versions change, so check the repository for the current list.
Read and write: Read and write: reads, searches, edits and deletes notes in the local vault.
-
list_files_in_vaultList files and folders at the vault root.
-
list_files_in_dirList files in one folder.
-
get_file_contentsRead the content of one note.
-
searchSearch all notes for matching text.
-
patch_contentInsert content next to a heading, block or frontmatter field.
-
append_contentAppend text to a new or existing note.
-
delete_fileDelete a note or folder.
Workflows
Example workflows
Prepare for a client meeting
-
1
Name the client.
-
2
The assistant searches the vault.
-
3
It reads related notes.
-
4
It summarizes history and open points.
-
5
It appends the summary to the meeting note.
Weekly review
-
1
Ask for notes created this week.
-
2
The assistant lists and reads them.
-
3
It groups ideas by theme.
-
4
It suggests links between notes.
-
5
You approve the edits.
Prompts
Example prompts
“Summarize everything in my vault about Harbor Group.”
“Append this idea to my Product Ideas note.”
“Which notes mention pricing but do not link to the Pricing Strategy note?”
Setup
Installation and configuration
Examples for Claude Desktop and Claude Code. Replace the placeholder values with your own keys, and store secrets outside version control.
Claude Desktop: claude_desktop_config.json
{
"mcpServers": {
"mcp-obsidian": {
"command": "uvx",
"args": [
"mcp-obsidian"
],
"env": {
"OBSIDIAN_API_KEY": "<YOUR_OBSIDIAN_API_KEY>",
"OBSIDIAN_HOST": "<your_obsidian_host>",
"OBSIDIAN_PORT": "<your_obsidian_port>"
}
}
}
}Claude Code: terminal
claude mcp add mcp-obsidian -e OBSIDIAN_API_KEY=<YOUR_OBSIDIAN_API_KEY> -e OBSIDIAN_HOST=127.0.0.1 -e OBSIDIAN_PORT=27124 -- uvx mcp-obsidian- Local server: PyPI: mcp-obsidian (run with uvx, stdio). Requires the Obsidian Local REST API community plugin..
- Needs: API key from the Obsidian Local REST API plugin (OBSIDIAN_API_KEY). Host defaults to 127.0.0.1, port 27124..
Security
Security considerations
-
Community code
Review the code and pin the version.
-
Back up the vault
Keep backups before letting it edit or delete.
-
API key
Protect the Local REST API key.
-
Personal data
Vaults often hold private notes. Limit what you connect.
Related servers
Servers that pair well with it
Notion
Notion's official hosted MCP server lets AI search and read pages, create and update pages and databases, query data and add comments.
Memory
The MCP project's Memory reference server gives AI a local knowledge graph to store people, things and facts and recall them later.
Readwise
Readwise's official hosted MCP server lets AI search and manage your reading highlights and Reader documents.
Keep exploring
Solutions and services that use it
Related services
View all related services- MCP integration Connect AI assistants to your CRM, files, databases and tools through Model Context Protocol servers, with safe permissions.
- RAG knowledge assistants Assistants that answer questions from your own documents and show where each answer came from.
- AI Product Development AI agents, knowledge assistants, copilots and document automation built into the way your team already works.
Solutions
View all solutions- Knowledge assistant (RAG) Ask a question in plain words and get an answer from your own documents, with links to the sources.
- Internal help desk assistant An assistant in Slack or Teams that answers policy and how-to questions from your handbooks and opens tickets when needed.
- Compliance tracking Track filing deadlines, licenses and obligations in one place, with reminders and AI summaries of relevant rule changes.
- Meeting notes automation Transcribe meetings and calls, summarize decisions and push action items into your CRM or project tool.
- AI sales research agent Short, sourced briefings on each prospect before a call, drafted by an AI agent from public information and your CRM.
- AI-assisted content workflows Briefs, first drafts, edits and repurposing in a workflow where people set the angle and approve every word.
Industries
View all industries- Healthcare Patient booking, intake forms, internal knowledge assistants and admin automation for clinics and care providers.
- Legal Contract review assistants, knowledge search, intake and document automation for law firms and in-house legal teams.
- Professional services Client portals, proposal drafting, knowledge assistants and internal tools for consultancies, agencies and firms.
- Education and elearning Course platforms, student portals, content workflows and AI tutoring assistants for schools and training companies.
Guides and articles
View all guides and articlesAI models
View all ai models- Cohere Rerank 4 Cohere's multilingual rerank models, which sort search results by relevance, in a best-quality Pro version and a low-latency Fast version.
- Gemini Embedding 2 Google's current embedding model, multimodal: it embeds text, images, video, audio and PDFs for search and retrieval.
- text-embedding-3-large OpenAI's most capable embedding model for search and retrieval, with 3,072-dimension vectors and support for English and other languages.
- text-embedding-3-small OpenAI's efficient, lowest-cost embedding model, with 1,536-dimension vectors for search, retrieval and similarity at scale.
- Cohere Embed v4 Cohere's multimodal embedding model for enterprise search, embedding text, images and mixed documents, with flexible vector sizes and long inputs.
- Voyage 4 Voyage AI's current embedding series, now part of MongoDB, with large, standard and lite models that share one embedding space.
Glossary terms
View all glossary terms- RAG RAG, or retrieval-augmented generation, is a method where an AI system first finds relevant passages in your documents, then answers using only those passages.
- Natural language processing Natural language processing is the field of AI that deals with understanding and generating human language, in text or speech.
- Semantic search Semantic search finds results by meaning rather than exact words, so a search for "reset my login" can find an article titled "Forgot your password".
- Chatbot A chatbot is software that holds a conversation with people through text or voice, answering questions or completing simple tasks.
- Embeddings Embeddings are lists of numbers that represent the meaning of text or images, so software can find items that are similar in meaning.
- Vector database A vector database stores embeddings, lists of numbers that represent meaning, and quickly finds the ones most similar to a query.
FAQ
Questions people ask us
Have a question that is not here? Ask us directly.
We did not find one at review time. This is a community server.
Obsidian's Local REST API plugin and its API key.
Yes. Back up your vault and review deletes.