Obsidian MCP Server: Connect an AI Assistant to Your Vault

An Obsidian MCP server lets your AI assistant read notes from your vault, search across them, and write new ones — all without leaving the session. You ask the assistant a question, it reads the relevant notes, and answers with the actual content of your knowledge base. Tools like fenbs complement this by keeping the shared work decisions and current tasks outside the vault, so every assistant can find both the reference notes and the agreed next steps in one session.

Obsidian does not have an official first-party MCP server, but the community has built several. They range from simple read-only note readers to full vault managers that can create, update, and link notes. The right choice depends on how much access you want to give an AI assistant and how you use the vault.

What an Obsidian MCP server can do

Most Obsidian MCP servers expose tools in two categories: search and retrieve, and write. Search tools let the assistant find notes by keyword, tag, or path and return the content. Write tools let it create new notes, append to existing ones, or update frontmatter. Some servers also expose the vault's link graph so the assistant can follow connections between notes.

The practical value is that the assistant can work with your actual notes rather than information you pasted into the chat. A research note, a meeting summary, or a template you wrote last year is available to the assistant without you having to find and copy it first.

Set clear access boundaries before connecting

Before connecting an assistant to a vault, decide exactly what it may read and write. A vault that contains personal notes, medical information, financial records, or confidential client information should not be fully exposed to an AI session without careful scoping. Most servers let you restrict access to a specific folder or set of folders. Use that feature.

• Limit read access to the folders the assistant actually needs for the work at hand.
• Restrict or disable write access unless you have a specific use case that requires it.
• Keep personally sensitive notes in a separate vault or folder outside the server's scope.
• Review what the assistant wrote before saving or syncing it — vault writes are persistent.

Connect the server

The most widely used community servers connect through the Obsidian Local REST API plugin, which exposes vault operations over HTTP on localhost. Install the plugin, enable it, and note the API key it generates. Then configure an MCP server that calls the plugin's endpoints. The MCP server acts as a bridge between the AI client and the REST API. An alternative approach is a server that reads the vault's markdown files directly from the filesystem using the file path.

Test the connection with a small, non-sensitive vault or a dedicated test folder first. Ask the assistant to list notes in a folder and confirm it returns the expected results before exposing your main vault.

Sync and conflicts

If your vault syncs with Obsidian Sync, iCloud, or another cloud service, writes made by the MCP server will sync to other devices. This is usually what you want, but it means the assistant's changes reach your phone or tablet immediately. If you are testing a write operation, do it in a folder that is excluded from sync, or use a dedicated test vault. Also confirm that simultaneous edits from the assistant and from another Obsidian instance do not produce conflicts — most sync services handle this, but the merge result may not be what you expected.

What to keep in Obsidian and what to keep in fenbs

Obsidian is strong for reference material: research notes, documentation, templates, and personal knowledge that you accumulate over time. fenbs is strong for work state: projects, tasks, decisions, rules, and where you left off. The two complement each other. Keep a detailed research note in Obsidian; keep the decision you reached based on that research in fenbs, linked to the task it informed.

The main reason to separate them is that your AI assistant needs both. It needs the source content from the vault and the agreed decisions and current tasks from fenbs. Having both available in a single session — one MCP server for notes, one for project state — means the assistant can answer questions about the research and also know what work is next.

How to use Obsidian with fenbs

Connect both an Obsidian MCP server and fenbs to your AI assistant. Use the vault for source content and fenbs for shared decisions and work state.

1. Create a free account and start a project for the work that uses the Obsidian notes. Describe what the vault contains and how the work uses it.
2. Write Decisions and rules for the access boundaries: which vault folders the assistant may read, whether it may write, and what to do if a note is unclear.
3. For each key conclusion drawn from vault notes, record it as an AI context note in fenbs so it persists across sessions without requiring the assistant to re-read the vault every time.
4. Connect both the Obsidian server and fenbs to your assistant via Integrations. Ask it to read the fenbs context first, then search the vault for specifics.
5. Before each session ends, save progress in fenbs so the next session knows where to start, even if it does not re-read the entire vault.