How to Use the Skalin MCP in Pydantic AI

Q: Can I list customer accounts using Pydantic AI and Skalin?

Yes. Use listcsaccounts. The tool delivers the account data, which Pydantic validates before your agent code ever sees it. This guarantees structural integrity for Skalin records.

Q: What happens if I need to get alerts with Pydantic AI?

The listcsalerts tool gets active warnings. Since the output is type-checked, you can immediately trust that the alert severity and description fields are correctly formatted.

Q: Is data privacy assured when using Skalin and Pydantic AI?

Yes. When your agent calls listaccountcontacts, only the contact information required by the schema is processed, ensuring that sensitive internal details remain protected.

Q: Which tools are available for Skalin and Pydantic AI?

The MCP Server provides many functions. You can use getaccounthealth, record history with loginteraction, or even modify tasks using updatecstask.

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Setup Skalin with Pydantic AI

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Verify Account Status via the MCP Server

Need to know if a client is active? The `get_api_status` tool provides connectivity details. Your agent calls this, and Pydantic AI ensures the response data structure matches your expected Python model. This guardrail means you never have to worry about unexpected field names or types coming back from Skalin.

Audit Account Activity on Pydantic AI

Looking at who's been using the platform? The `list_account_metrics` function fetches usage data. Because of type validation, you know exactly what metrics are included and how they are formatted. This level of guaranteed correctness is why Pydantic AI shines for mission-critical systems.

Manage User Lists with the MCP Server

If you need to see who manages a client's account, run `list_success_managers`. The tool returns a list of users. Pydantic AI validates this output against a strict schema, preventing runtime errors. It enforces that every field—from username to role—is exactly what you expect.

Setup guide

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

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

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

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Common questions about Skalin MCP in Pydantic AI

The framework validates every response against a defined model. If the underlying MCP Server returns a string where an integer is expected, your agent fails loudly with a clear validation error.

Yes. Use `list_cs_accounts`. The tool delivers the account data, which Pydantic validates before your agent code ever sees it. This guarantees structural integrity for Skalin records.

The `list_cs_alerts` tool gets active warnings. Since the output is type-checked, you can immediately trust that the alert severity and description fields are correctly formatted.

Yes. When your agent calls `list_account_contacts`, only the contact information required by the schema is processed, ensuring that sensitive internal details remain protected.

The MCP Server provides many functions. You can use `get_account_health`, record history with `log_interaction`, or even modify tasks using `update_cs_task`.

Use it with your favorite AI tools

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