How to Use the Colossyan MCP in Pydantic AI
Build type-safe video workflows using Pydantic AI to validate Colossyan video schemas before they render.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Colossyan MCP to Pydantic AI
Create your Vinkius account to connect Colossyan 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.
Type-Safe Video Generation
`generate_video` ensures that your Pydantic AI agent validates the entire JSON Colossyan video descriptor against strict Python schemas before sending it to the server. If the Pydantic AI agent attempts to pass an invalid Colossyan layout or missing field, the execution fails immediately. This strict checking prevents wasted Colossyan API credits on malformed video requests. Your Pydantic AI agent can safely monitor the rendering process using `get_job_status` knowing the input data was completely accurate.
Pydantic AI Avatar and Voice Auditing
`list_actors` allows your Pydantic AI agent to fetch all available Colossyan workspace avatars and validate their IDs against your application's internal models. This prevents your Pydantic AI agent from referencing non-existent Colossyan actors during video generation steps. The same strict type-safety applies to Colossyan audio assets. Your Pydantic AI agent queries `list_voices` to ensure the selected voice matches your strict locale requirements, failing loudly if the Colossyan API returns an unexpected voice format.
Validated Draft Creation
`generate_draft` lets your Pydantic AI agent convert raw markdown or text into structured Colossyan drafts while enforcing runtime types. The Pydantic AI framework guarantees that the text blocks and scenes match the exact structure Colossyan expects. If a Colossyan draft contains errors, the Pydantic AI agent uses `delete_video` or `delete_job` to clean up the workspace. This keeps your Colossyan video production pipeline free of broken or incomplete drafts.
Set up Colossyan 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 deprecatedMCPServerHTTPclass with full protocol support. - 2
Configure the FastMCPToolset
Pass a JSON-style config dict to
FastMCPToolsetwith 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 callagent.run(). Swapopenai:gpt-4ofor any supported model — Anthropic, Google, Mistral, or Groq.
from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset
toolset = FastMCPToolset({
"mcpServers": {
"colossyan-mcp": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
})
agent = Agent(
"openai:gpt-4o",
toolsets=[toolset],
system_prompt="You have access to Colossyan tools.",
)
result = await agent.run("List recent Colossyan transactions")
print(result.output) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Colossyan. 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.
Why Choose Vinkius
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lower AI costs
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Common questions about Colossyan MCP in Pydantic AI
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