How to Use the Easelly MCP in Pydantic AI

Q: How do I initialize Easelly inside a Pydantic AI agent?

Use the unified MCPToolset class with your Vinkius HTTP endpoint. Pass the toolset in the toolsets argument when building your agent.

Build type-safe visual workflows with Pydantic AI validating every Easelly design update at runtime.

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Connect Easelly MCP to Pydantic AI

Create your Vinkius account to connect Easelly 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 Easelly with Pydantic AI

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Validate infographic structures with Pydantic AI

The `generate_json` tool extracts the precise layout schema of your design template. When paired with Pydantic AI, this JSON is immediately validated against your Python type models to prevent structural errors. If the layout properties deviate from your expected schema, this MCP Server integration triggers a loud validation error. This prevents your agent from attempting to edit corrupted design files.

Ensure type-safe design updates and creations

The `update_infographic` tool applies changes to your visual assets only after Pydantic AI validates the input payload. This guarantees that your agent never sends malformed coordinates or invalid color codes to the API. For new assets, the agent executes `create_infographic` using strictly typed parameters. If the model tries to pass a string where an integer is required, the execution halts before making the API call.

Export verified PDFs and images without silent failures

The `generate_pdf` tool outputs clean, print-ready documents based on your validated templates. Pydantic AI checks the output file path and status code to ensure the export succeeded. The agent can also call `generate_image` or `list_infographics` to manage your visual library. Every response is parsed through Pydantic models, giving you 100% confidence in the state of your design assets.

Setup guide

Set up Easelly 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": {
        "easelly-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Easelly MCP in Pydantic AI

Use the unified `MCPToolset` class with your Vinkius HTTP endpoint. Pass the toolset in the `toolsets` argument when building your agent.

The framework raises a validation error immediately. This prevents your agent from working with malformed JSON structures.

Yes. Pydantic AI supports both Streamable HTTP and SSE transports for connecting to external server deployments.

Yes. You can use this toolset with OpenAI, Anthropic, or local models while maintaining strict type-safety for all infographic operations.

All validation occurs locally within your Python runtime. The server only receives standard HTTPS requests for operations like `generate_json`, secured by Vinkius's zero-trust infrastructure.

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