How to Use the Sirv MCP in Pydantic AI

Q: How do I get detailed usage data with Sirv and Pydantic AI?

You use getdetailedusage. This provides metrics like bandwidth throughput and request counts, giving you validated, structured data that your agent can process without error.

Q: Can I list all users in my account using Sirv and Pydantic AI?

Yes. The agent runs listaccountusers to pull a definitive list of every user associated with the Sirv account, ensuring your data models are populated correctly.

Q: Does this MCP Server help with file management for Sirv and Pydantic AI?

It does. You can use searchfiles to find metadata or readdirectory to list contents, all of which return structured data that Pydantic validates before your agent acts on it.

Q: What's the safest way to check Sirv billing info with Pydantic AI?

The getbillinginfo tool retrieves the data, and because of Pydantic's validation, you know exactly what fields you'll receive—no unexpected junk data.

Ensure perfect data integrity with Sirv CDN tools using Pydantic AI.

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…and any MCP-compatible client

MCP Servers — Included with Plan

Connect Sirv MCP to Pydantic AI

Create your Vinkius account to connect Sirv to Pydantic AI — we handle the hosting, security, and runtime updates so you don't have to. No server setup required.

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Setup Sirv with Pydantic AI

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Claude

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Gemini

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Monitor Usage Metrics

The agent calls `get_detailed_usage` to pull metrics on how Sirv is being used. This gives you specific data points, like bandwidth throughput and request counts, which are necessary for accurate reporting. It also lets you check total usage with `get_account_stats`, giving a reliable overview of both storage capacity and current traffic volume.

Manage Sirv Assets

If you need to find files or folders, the agent runs `search_files` for metadata and URLs. You can also use `read_directory` when given an absolute path starting with '/'. Got a file that needs deleting? The server handles permanent deletion via `delete_file`; just remember it's irreversible.

Audit Account Structure

The agent can list every user on your account using `list_account_users`, and you can see configured domains with `list_custom_domains`. This helps keep track of permissions. Whenever you need a financial check, the `get_billing_info` tool retrieves all necessary billing details.

Setup guide

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

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

result = await agent.run("List recent Sirv 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 Sirv. 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 Sirv MCP in Pydantic AI

You use `get_detailed_usage`. This provides metrics like bandwidth throughput and request counts, giving you validated, structured data that your agent can process without error.

Yes. The agent runs `list_account_users` to pull a definitive list of every user associated with the Sirv account, ensuring your data models are populated correctly.

It does. You can use `search_files` to find metadata or `read_directory` to list contents, all of which return structured data that Pydantic validates before your agent acts on it.

It handles account metadata, usage stats (bandwidth/traffic), billing records, and file system details. Everything is structured so your agent always gets predictable input.

The `get_billing_info` tool retrieves the data, and because of Pydantic's validation, you know exactly what fields you'll receive—no unexpected junk data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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