Obsidian Publish MCP for AI Agents. Deeply Index Your Markdown Knowledge Base
Obsidian Publish MCP lets your AI agent read every note in your published markdown knowledge base. It indexes your entire site structure and pulls the raw text content of specific documents so you can summarize years of notes or cross-reference complex technical specs instantly. You get deep access to structured, private, or public writing.
Give Claude and any AI agent real-world access
The MCP generates a structural map of all notes, showing how they link together in a navigable tree.
You get the complete text and any associated assets for a specified note or file path.
The system pulls technical data about notes, including creation dates, tags, and frontmatter fields.
You can check the global configuration of your Obsidian Publish endpoint to confirm connectivity status.
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What AI agents can do with Obsidian Publish MCP: 5 Tools
These tools let your AI client perform specific actions on your site, including listing files, checking metadata, and retrieving the raw content of any note.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Obsidian Publish MCPList Files
Lists all the file paths that have been explicitly published in your Obsidian workspace.
Get File
Retrieves the full, raw markdown text and any associated binary files for a specific...
Site Info
Checks global configuration details and styling used across your entire published...
List Navigation
Visualizes the structured, linked map of markdown notes within your vault.
Get Metadata
Extracts technical properties from a note, including tags, creation dates, and...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Obsidian Publish, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Obsidian Publish. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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The pain of navigating thousands of notes Solved with Vinkius AI Gateway
You know the drill: you sit down to write something big. You need to reference that character detail from your 'Year 2' folder, cross-check a technical spec from the 'Architecture' section, and pull the official process outline from 'SOPs'. What happens? You open Obsidian, jump between dozens of tabs, copy snippets here, paste context there, and spend more time managing the source material than actually writing.
With this MCP, you stop clicking. You just tell your agent what you need. It handles the mapping process by utilizing its ability to list files and crawl navigation trees. The result? A single, synthesized answer that pulls accurate context from across your entire markdown vault.
Obsidian Publish MCP: Structured Knowledge Retrieval
Before this, gathering all the pieces involved opening multiple notes and manually tracking which file contained which piece of information. It was slow, prone to error, and required constant context switching.
Now, you connect your source and let the agent do the heavy lifting. You get structured data streams—the full content of a note via `get_file` or its technical properties using `get_metadata`. Your focus shifts entirely from file management to critical thinking.
What your AI can actually do with this
Your personal vault—the thousands of scattered markdown files across Obsidian Publish—is suddenly connected to your AI client. Instead of opening dozens of tabs and manually copy-pasting sections, your agent now sees the whole picture. It can build a functional map of your entire knowledge base by crawling the navigation structure and listing all available file paths.
Need to summarize one specific document? You just ask for it, and the raw text streams directly into your chat window. This capability means you don't have to navigate complex local folders; you talk about your notes like they're in a database. Connecting this MCP through Vinkius gives your agent access to deep file content, technical metadata, and even site configuration details—all so you can finally build that smart chatbot or research assistant based on your own work.
019d75e1-e432-734c-9236-0c91927db387 Here's how it actually works
The bottom line is that your AI client treats your entire private markdown vault like one searchable knowledge graph.
Subscribe to this MCP and input your specific Obsidian Publish Site ID (and an optional token if the vault is private).
Tell your AI agent what you want to know—for example, 'Summarize all notes related to Q3 marketing goals.'
The agent executes multiple background calls to read the structure, pull raw content, and synthesize a single answer for you.
Who is this actually for?
This connector is built for technical writers, academics, and internal documentation specialists. If your job involves synthesizing information from hundreds of linked notes or maintaining complex standard operating procedures (SOPs), you'll need this.
Using the MCP, they ask their agent to cross-reference product requirements across dozens of internal documents and pull only the relevant code snippets into a single draft.
They use it to analyze years of personal notes, asking the AI to find all mentions of 'quantum computing' or track character development across an entire fictional series without manually opening every file.
They connect their team's SOP vault and use it to build a chatbot that rapidly summarizes complex, multi-step procedures for new hires.
What Changes When You Connect
Cross-reference complex ideas across your entire vault. Instead of hunting through files, you ask the agent to pull data from multiple sources and summarize them for you.
Audit your notes instantly. Use the MCP's ability to extract internal properties and metadata so you know exactly what tags or dates are attached to a piece of information.
Build corporate knowledge assistants. Feed your team's standard operating procedures into the AI, letting it rapidly answer questions about processes without requiring manual search queries.
Access raw content reliably. With get_file, you get the clean markdown source for any note, perfect for feeding specific code snippets or technical passages to other tools.
Understand site architecture. Use list_navigation to visualize your notes' relationship map, ensuring that no major section of your work is accidentally orphaned from the main structure.
See it in action
Need a summary of all characters in my novel.
Instead of opening every character profile note and manually reading through them, you tell your agent to use list_files to find all 'character' notes, and then uses those paths with the raw content retrieval to build a cross-referenced timeline for you.
The team needs an SOP chatbot.
You connect the MCP and ask it to ingest your entire documentation set. The agent can then answer, 'What is step 3 of the deployment process?' by querying the correct file's raw content.
Checking if a note was properly categorized.
You use get_metadata on a specific note to confirm its status, tags, and internal links. This confirms whether it's ready for publishing or needs more context before being referenced.
Pulling all code examples from my technical documentation.
You ask the agent to analyze your 'developer guide' vault, which uses list_files to identify all .md files, and then executes get_file on each one to extract only the markdown fenced code blocks for review.
The honest tradeoffs
What to watch out for, and the recommended way to handle each one.
Asking a general question about your notes
Prompting: 'What's my company policy?' The agent might hallucinate or give vague answers because it doesn't know which specific file to read.
First, use list_navigation to narrow down the relevant section (e.g., 'HR Policies'). Then, ask the agent to focus its search and retrieval only on those files.
Assuming all notes are published
Asking the AI about a note that exists in your local vault but isn't properly linked or published on Obsidian Publish.
Always start by running list_files to confirm which files are actually exposed and indexed by the MCP before asking for content.
Copying large blocks of text manually
Manually opening 15 different notes, copying a key paragraph from each, and pasting them into a summary document.
Let your agent handle it. Tell the MCP to retrieve specific files using get_file and ask it to summarize those contents in one go.
When It Fits, When It Doesn't
Use this MCP if your core problem is knowledge retrieval from a structured, markdown-based source. You need deep access—meaning you're not just looking for keywords; you need the raw text and structural context of the notes themselves. The best indicator is when you find yourself having to jump between 10+ tabs to assemble an answer. Don't use this if you simply need a general web search, or if your content lives in unstructured formats (like PDFs that aren't markdown). If your data source is more like a spreadsheet and needs querying by column headers, you should look for a database connector instead.
Questions you might have
How does Obsidian Publish MCP handle private vaults? +
You must provide your Obsidian Publish Site ID and an optional access token for the agent to read notes in private or restricted corporate vaults. This keeps your data secure.
Can Obsidian Publish MCP index code snippets? +
Yes. The get_file tool retrieves the full raw markdown content, which includes any markdown-fenced code blocks and technical code examples housed in your notes.
Is this only for published sites? +
No, it connects to your established Obsidian Publish environment. The MCP indexes files that are already structured within the publishing framework.
What is the difference between list_files and list_navigation? +
List files gives a simple directory of every available file path. List navigation provides a visual, linked map showing how those notes relate to each other structurally within your vault.
Does Obsidian Publish MCP only read markdown? +
It reads the raw markdown content and can retrieve associated binary assets that are embedded or referenced in your published notes.