How to Use the Miro (Visual Collaboration & Whiteboarding) MCP in Pydantic AI

Build type-safe Pydantic AI workflows that validate Miro board data and sticky notes at runtime before execution.

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Connect Miro (Visual Collaboration & Whiteboarding) MCP to Pydantic AI

Create your Vinkius account to connect Miro (Visual Collaboration & Whiteboarding) 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.

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Setup Miro (Visual Collaboration & Whiteboarding) with Pydantic AI

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Pydantic AI MCP Server Board Generation

The `create_board` tool initializes a collaborative canvas with strict parameter validation. When your agent calls this tool, Pydantic AI validates the board name and configuration against strict schemas, preventing malformed API requests. If the board creation response contains unexpected fields, the framework raises a validation error immediately. This stops downstream code from breaking and ensures your application state remains clean.

Strict Sticky Note Validation

The `create_sticky_note` tool places text elements onto your board at specific coordinate points. Your agent uses this tool to place user feedback, with the framework validating the exact text length and coordinate types before the API call. This prevents the agent from passing invalid coordinates or empty text strings. You avoid runtime API failures because the validation happens locally in your Python environment.

Board Structure Auditing

The `get_board` tool retrieves the static configuration of a specific canvas to inspect its settings. Your agent calls this tool to verify the board exists and is accessible before attempting to write new elements. The returned JSON is parsed directly into a Pydantic model, ensuring that properties like board ID and sharing permissions are typed correctly before your business logic processes them.

Setup guide

Set up Miro (Visual Collaboration & Whiteboarding) 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-visual-collaboration-whiteboarding-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

result = await agent.run("List recent Miro (Visual Collaboration & Whiteboarding) transactions")
print(result.output)

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Common questions about Miro (Visual Collaboration & Whiteboarding) MCP in Pydantic AI

Instantiate MCPToolset with the Vinkius HTTP URL and pass it to the agent's toolsets list. This exposes the entire suite of 8 tools, including create_board and list_items, directly to your agent.

The framework will fail loudly with a validation error. This prevents silent failures and ensures your agent never processes corrupt metadata when executing tools like list_members.

Yes, Pydantic AI is model-agnostic. You can pair this server with local models or commercial APIs to run tools like create_shape and list_tags using the same type-safe interface.

No, you should use the unified MCPToolset approach as recommended by the latest Pydantic AI documentation for connecting to external HTTP servers.

Every request containing board lists, shape structures, or sticky notes is processed within an isolated V8 sandbox. This MCP setup guarantees your API keys are hidden and tokens are injected securely at the edge.

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