Can the AI accurately recreate the folder structure of my vault?

Yes. When the model invokes `list_navigation`, it downloads the systematic JSON map of the entire public vault, thereby allowing it to understand the relationships and physical structure of your folders perfectly.

Does `get_file` automatically render complex Markdown components?

No rendering is performed on our end. The `get_file` tool returns pure raw Markdown (including frontmatter and obsidian syntax). Fortunately, LLMs (like Claude) are exceptionally adept at reading and reasoning over raw Markdown text structures.

If my Published site is private and requires a password, does it still work?

Yes, it works gracefully. If you configured Obsidian Publish with restricted read access, you can manually inject a persistent token into the setup, giving your AI agent the clearance to read securely behind the authentication wall.

Obsidian Publish MCP Server for Pydantic AI 5 tools — connect in under 2 minutes

Name: Obsidian Publish
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 5 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Obsidian Publish through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Obsidian Publish "
            "(5 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Obsidian Publish?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Obsidian Publish MCP Server

Connect your Obsidian Publish environment to your AI agent and construct an intelligent oracle that reads smoothly from your personal or corporate markdown knowledge base.

Pydantic AI validates every Obsidian Publish tool response against typed schemas, catching data inconsistencies at build time. Connect 5 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

Vault Crawling — Programmatically fetch your entire published vault structure utilizing list_files and list_navigation to build contextual trees.
Direct Note Access — Execute get_file to stream the complete raw markdown contents of any note directly into your chat workflow for fast summarization.
Metadata Operations — Use get_metadata to retrieve frontmatter properties, tags, and internal link logic mapped by Obsidian.
Site Auditing — Easily ping site_info to ensure connectivity and verify the deployment status of your target Obsidian publish endpoint.

The Obsidian Publish MCP Server exposes 5 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Obsidian Publish to Pydantic AI via MCP

Follow these steps to integrate the Obsidian Publish MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 5 tools from Obsidian Publish with type-safe schemas

Why Use Pydantic AI with the Obsidian Publish MCP Server

Pydantic AI provides unique advantages when paired with Obsidian Publish through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Obsidian Publish integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Obsidian Publish connection logic from agent behavior for testable, maintainable code

Obsidian Publish + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Obsidian Publish MCP Server delivers measurable value.

Type-safe data pipelines: query Obsidian Publish with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Obsidian Publish tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Obsidian Publish and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Obsidian Publish responses and write comprehensive agent tests

Obsidian Publish MCP Tools for Pydantic AI (5)

These 5 tools become available when you connect Obsidian Publish to Pydantic AI via MCP:

get_file

Retrieve exact textual file content and binary assets

get_metadata

Extract internal creation hashes mapping a specific Markdown page

list_files

List all explicitly published raw file paths across the Obsidian workspace

list_navigation

Visualize structurally formatted Markdown navigation trees

site_info

Identify global configuration and styling mapping the site

Example Prompts for Obsidian Publish in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Obsidian Publish immediately.

"Check the vault and list all the files currently publicly available."

"Read the contents of 'System Requirements 2026.md'."

"Fetch the metadata and tags applied to my 'Inbox' note."

Troubleshooting Obsidian Publish MCP Server with Pydantic AI

Common issues when connecting Obsidian Publish to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Obsidian Publish + Pydantic AI FAQ

Common questions about integrating Obsidian Publish MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Obsidian Publish MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.