How to Use the Dribbble MCP in Pydantic AI

Q: Can I use Pydantic AI to monitor my Dribbble portfolio activity?

You can call listusershots to retrieve your feed. Pydantic AI maps the response to a model, making it easy to check your data status.

Manage Dribbble shots with Pydantic AI. Get runtime validation for every portfolio action and ensure your data stays clean.

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Connect Dribbble MCP to Pydantic AI

Create your Vinkius account to connect Dribbble 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 Dribbble with Pydantic AI

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Type-safe shot creation with Pydantic AI

Use `create_shot` to publish work to your Dribbble profile. Pydantic AI validates the structure of your data at runtime, preventing invalid fields from reaching the API. If your input doesn't match the required schema, the agent stops before making the call. It prevents corrupt data from entering your portfolio.

Structured project management

Use `create_project` and `update_project` to manage your portfolio collections. The framework ensures every project update adheres to your defined model. This approach eliminates silent errors. You get an immediate validation failure if your project data is missing a required property.

Granular shot and attachment control

Use `update_shot` to modify existing entries with confidence. Pydantic AI checks the data types of your updates before the tool executes. You can also manage files with `create_attachment` and `delete_attachment`. Every operation is checked against the schema to ensure consistent portfolio management.

Setup guide

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

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

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

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Common questions about Dribbble MCP in Pydantic AI

The framework validates your input against the tool schema. If your shot data misses a required field, Pydantic AI stops the request to protect your Dribbble profile.

You can call `list_user_shots` to retrieve your feed. Pydantic AI maps the response to a model, making it easy to check your data status.

You add the Dribbble MCP toolset to your agent configuration. The framework handles the communication with the server and validates all responses.

It provides strict type-checking, which prevents malicious or malformed data from being sent. Your authentication is managed by the secure Vinkius endpoint.

Your metadata is processed in memory by your agent. No Pydantic AI user data is stored on our servers; we only provide the secure connection to the Dribbble API.

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