How to Use the Dub.co MCP in Pydantic AI

Q: How do I set up the Dub.co MCP Server with Pydantic AI?

Install the slim package using pip install "pydantic-ai-slimmcp" and initialize the MCP toolset with your Vinkius HTTP endpoint. Pass this toolset into the toolsets argument of your Pydantic AI Agent.

Q: Does Pydantic AI support SSE transports for the Dub.co server?

Yes, the unified MCPToolset class in Pydantic AI supports both Streamable HTTP and SSE transports. You simply pass the external server URL, and the framework handles the underlying communication protocol automatically.

Q: Can I use Pydantic AI to safely delete links via Dub.co?

Yes, your Pydantic AI agent can call the deleteshortlink tool. Because Pydantic AI enforces type checks, you can be sure the target ID matches the expected string format before executing the deletion.

Build type-safe Pydantic AI workflows that validate every Dub.co short link and analytic response at runtime.

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Create your Vinkius account to connect Dub.co 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 Dub.co with Pydantic AI

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Type-safe link creation with Pydantic AI

The `create_short_link` tool executes with strict schema enforcement, ensuring your Pydantic AI agent never sends malformed destination URLs to Dub.co. If your model attempts to pass an invalid domain, the Pydantic AI framework throws a validation error before the API call is made. You initialize this by passing the MCP toolset to your Pydantic AI `Agent` constructor. The Pydantic AI agent relies on these strict types to guarantee that every link generated fits your application's expected configuration exactly.

Strict validation for workspace analytics in Pydantic AI

The `get_workspace_analytics` tool returns structured metrics that the Pydantic AI framework validates against Pydantic schemas at runtime. This prevents silent failures or hallucinated metrics from corrupting your internal dashboards. Your Pydantic AI agent uses these validated metrics to make decisions, like calling the `update_short_link` tool to fix broken paths. Because the data is typed, you can safely write downstream Python logic in Pydantic AI without worrying about missing dictionary keys.

Safe domain and tag discovery via MCP Server

The `list_domains` tool helps your Pydantic AI agent discover active routing domains before attempting to create new short URLs. Your agent combines this with the `list_tags` tool to enforce strict organizational rules across your workspace. This MCP Server integration supports both Streamable HTTP and SSE transports. Your Pydantic AI agent can query the `get_url_metatags` tool to verify Open Graph tags, ensuring your social sharing cards look correct before you publish.

Setup guide

Set up Dub.co 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": {
        "dubco-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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

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Common questions about Dub.co MCP in Pydantic AI

Install the slim package using `pip install "pydantic-ai-slim[mcp]"` and initialize the MCP toolset with your Vinkius HTTP endpoint. Pass this toolset into the `toolsets` argument of your Pydantic AI `Agent`.

The Pydantic AI framework will fail loudly with a validation error rather than passing corrupt data to your model. This ensures that tools like `get_link_details` only return verified, correctly typed objects.

Yes, the unified `MCPToolset` class in Pydantic AI supports both Streamable HTTP and SSE transports. You simply pass the external server URL, and the framework handles the underlying communication protocol automatically.

Yes, your Pydantic AI agent can call the `delete_short_link` tool. Because Pydantic AI enforces type checks, you can be sure the target ID matches the expected string format before executing the deletion.

Vinkius isolates your connection inside a secure, ephemeral V8 sandbox that executes each tool call independently. Your short link definitions and workspace metadata are processed in-memory and never stored on disk.

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