How to Use the Cloud BOT MCP in Pydantic AI

Use Pydantic AI to build type-safe automation with the Cloud BOT MCP Server.

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Connect Cloud BOT MCP to Pydantic AI

Create your Vinkius account to connect Cloud BOT 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 Cloud BOT with Pydantic AI

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Claude

Perplexity

Type-validated bot execution

Invoke `execute_bot` and rely on Pydantic models to validate the input structure at runtime. If the bot response deviates from your schema, the agent catches the error immediately instead of passing bad data through your logic. This enforces strict contracts between your agent and the cloud bots. You get reliable, typed responses every time an operation finishes.

Monitor status with strict types

Fetch job states using `get_job_status` and map the output directly to a Pydantic model. Your agent logic waits for a valid status before continuing to the next step of your workflow. No more silent failures or empty fields. You define exactly what a 'success' looks like, and the MCP server satisfies that requirement.

Browse available cloud bots

Call `list_bots` to get a list of registered automation scripts. The agent parses this list into a typed sequence, ensuring it only selects bots that match your current processing needs. This keeps your agent’s choices grounded in reality. It only attempts to run bots that are actually available and identified by your schema.

Setup guide

Set up Cloud BOT 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": {
        "cloud-bot-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

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

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

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Common questions about Cloud BOT MCP in Pydantic AI

Install the pydantic-ai-slim package and configure an MCPToolset with your endpoint. Pass this toolset into your agent to enable type-safe tool execution.

Yes, it provides the raw response which your Pydantic models then validate. If the data is missing or wrong, the agent will throw a validation error before processing continues.

The server is model-agnostic. You can swap between OpenAI, Anthropic, or local models, and your Pydantic validation will remain consistent.

You can manage tool list caching in your client configuration. This improves performance for agents that call the server frequently.

We secure all interactions via Vinkius managed endpoints. The server only touches the specific job logs and output files required for your defined tasks.

Use it with your favorite AI tools

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