How to Use the Transloadit MCP in Pydantic AI

Q: What's the best practice for managing media workflows using Transloadit and Pydantic AI?

Use createprocessingtemplate to build your workflow steps first. This keeps the logic clean, and since everything is typed, you eliminate entire classes of runtime errors.

Q: Can I use Pydantic AI to audit complex file processing jobs with Transloadit?

Yes. You can get job details using getassemblydetails or view the history via listassemblies. The data returned is always validated, giving you high confidence in your audit records.

Q: If I need usage reports for Transloadit with Pydantic AI, which tool should I use?

Use getbillingusage, passing the YYYY-MM format. This method returns file processing usage and costs that are validated against your defined schema.

Build reliable media agents with Pydantic AI. Use Transloadit to process files, knowing every output is type-safe.

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Connect Transloadit MCP to Pydantic AI

Create your Vinkius account to connect Transloadit 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 Transloadit with Pydantic AI

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Type-Safe Pipeline Execution

When your agent runs a workflow, it calls `create_assembly` with the steps JSON. The benefit here? Even if the API response structure is wrong, Pydantic validates everything at runtime. You won't get silent data corruption; you'll fail loudly. You can also manage complex logic by calling `list_assemblies`, ensuring your agent only processes valid job IDs.

Schema-Validated Templates

Set up reusable media blueprints using `create_processing_template`. The entire JSON template is treated as a structured data object, which Pydantic can validate against. This means your templates are inherently correct. The toolset also allows you to retrieve the configuration of any saved job with `get_template_details`, providing validated data about that specific processing setup.

Reliable Reporting and Auditing

Monitoring costs is crucial. The agent uses `get_billing_usage` to retrieve file processing usage and costs for a given YYYY-MM month. Because Pydantic validates the output, you know this billing data is correct. Need to retry an old job? Call `replay_assembly`. If you want just a list of recent jobs, `list_assemblies` handles that.

Setup guide

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

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

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

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Common questions about Transloadit MCP in Pydantic AI

You pass the MCP Toolset to your Agent. The key advantage is that every time a tool like `create_assembly` runs, Pydantic validates the returned data against defined models, guaranteeing correctness.

Use `create_processing_template` to build your workflow steps first. This keeps the logic clean, and since everything is typed, you eliminate entire classes of runtime errors.

Yes. You can get job details using `get_assembly_details` or view the history via `list_assemblies`. The data returned is always validated, giving you high confidence in your audit records.

Use `get_billing_usage`, passing the YYYY-MM format. This method returns file processing usage and costs that are validated against your defined schema.

This server deals with financial records related to media encoding. The `get_billing_usage` tool reports on file processing usage and costs, ensuring that the billing data you receive is always correctly structured.

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