How to Use the Daktela MCP in Pydantic AI

Q: How do I set up the Daktela integration in Pydantic AI?

Install the pydantic-ai-slimmcp package, then initialize MCPToolset pointing to your Vinkius Daktela endpoint. Pass the toolset into your Pydantic AI Agent's toolsets argument to register all Daktela tools.

Q: How does the framework protect my Daktela ticket data?

Daktela ticket details processed by getticket and createticket are validated in memory and never stored in Pydantic AI logs. All traffic runs through encrypted SSE or HTTP channels with strict token authentication.

Build type-safe Daktela workflows in Pydantic AI that validate every ticket and contact at runtime.

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Setup Daktela with Pydantic AI

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Validate Daktela tickets using Pydantic AI

The `create_ticket` tool executes within a strict Pydantic AI environment where every Daktela field is validated against Pydantic models. If your Pydantic AI agent tries to submit a Daktela ticket with a missing subject, the framework fails loudly. You use `get_ticket` to pull Daktela ticket details, converting raw JSON payloads into validated Pydantic AI models. This prevents corrupt Daktela data from breaking your downstream Pydantic AI application logic.

Enforce strict schemas on CRM contact creation

The `create_contact` tool ensures that new Daktela customer profiles match your exact Pydantic AI schema. If the model-agnostic agent generates an invalid phone format, Pydantic AI rejects the payload before it hits Daktela. Your Pydantic AI agent uses `list_contacts` to search existing Daktela records. The returned Daktela list is validated at runtime, ensuring your Pydantic AI pipeline only processes properly structured customer data.

Audit email history with type-safe schemas

The `list_email_history` tool pulls Daktela communication logs into your Pydantic AI agent. The Pydantic AI framework validates the Daktela email metadata, verifying that timestamps and sender addresses conform to your strict types. Your Pydantic AI agent pairs this with `list_activities` to build a clean timeline of Daktela customer interactions. This guarantees that your Pydantic AI models never ingest malformed Daktela activity logs.

Setup guide

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

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

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

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Common questions about Daktela MCP in Pydantic AI

Install the `pydantic-ai-slim[mcp]` package, then initialize `MCPToolset` pointing to your Vinkius Daktela endpoint. Pass the toolset into your Pydantic AI Agent's `toolsets` argument to register all Daktela tools.

The Pydantic AI framework raises a validation error immediately at runtime. This prevents your agent from making decisions based on malformed or corrupted Daktela ticket data.

Yes, Pydantic AI is model-agnostic. You can connect this Daktela server to local models or commercial APIs while maintaining strict schema enforcement.

The Pydantic AI toolset supports both Streamable HTTP and SSE transports. Ensure your external MCP Server is running before initializing the connection.

Daktela ticket details processed by `get_ticket` and `create_ticket` are validated in memory and never stored in Pydantic AI logs. All traffic runs through encrypted SSE or HTTP channels with strict token authentication.

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