How to Use the Miro MCP in Pydantic AI

Q: How does the agent handle deleting board items safely?

The agent must call deleteboarditem with a validated board ID and item ID over the MCP Server setup. Because this action is irreversible, you can wrap the tool in a Pydantic validator to require human approval.

Build type-safe Pydantic AI workflows that validate Miro board mutations and canvas updates at runtime.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect Miro MCP to Pydantic AI

Create your Vinkius account to connect Miro to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup Miro with Pydantic AI

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Validate Miro board items with Pydantic AI

`get_board_item` returns structured JSON that your Pydantic AI models validate against strict Python schemas at runtime. This prevents your agent from processing corrupted data or hallucinating card properties when reading from the canvas. If your agent needs to inspect multiple elements, `list_board_items` pulls all widgets from the board and parses them into typed objects via the active MCP connection. This guarantees that fields like position coordinates and text content are fully validated before your application logic runs.

Execute type-safe canvas writes using this MCP Server

`create_sticky_note` and `create_card` require precise coordinate inputs and text parameters that your agent validates before sending the request. If the LLM generates a malformed payload, Pydantic AI catches the validation error before making the API call, saving you token costs. When creating new workspaces, `create_board` returns a strongly typed board object containing validated view and edit links. If you need to modify board metadata, `update_board` ensures only valid string fields are sent to the Miro API.

Manage board access with strict type checks

`add_board_member` strictly validates user IDs and roles before granting access to a board. The agent lists current collaborators using `list_board_members` and parses the output into a type-safe list to prevent privilege escalation. For communication, the agent uses `create_comment` and `list_comments` to manage feedback threads with guaranteed schema compliance. The agent checks its own credentials using `get_user_context` to verify that the active session matches your security policy.

Setup guide

Set up Miro MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "miro-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Miro tools.",
)

result = await agent.run("List recent Miro transactions")
print(result.output)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Miro. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect Miro now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about Miro MCP in Pydantic AI

Use the unified MCPToolset class pointing to your Vinkius server URL and pass it to the agent's toolsets parameter. This registers all 14 tools and automatically builds the underlying validation schemas.

The framework raises a validation error immediately, stopping the agent from acting on corrupt data. This is crucial when processing complex board items via `list_board_items`.

Yes, you can configure your agent's system prompt or filter the toolset to only expose query tools like `list_boards` and `get_board`.

The agent must call `delete_board_item` with a validated board ID and item ID over the MCP Server setup. Because this action is irreversible, you can wrap the tool in a Pydantic validator to require human approval.

Vinkius executes the server within a zero-trust, ephemeral V8 sandbox. Your board layouts, comment histories, and membership permissions are never stored, and all API traffic is isolated to your specific session token.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript