Domo MCP Server for Pydantic AIGive Pydantic AI instant access to 6 tools to Add User To Group, Create Group, Create User, and more

Name: Domo
Price: 29 USD
Availability: InStock
Rating: 0.2 (1 reviews)
Author: Vinkius

GDPR Free for Subscribers

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Domo through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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The Domo MCP Server for Pydantic AI is a standout in the Brain Trust category — giving your AI agent 6 tools to work with, ready to go from day one.

Built for AI Agents by Vinkius

Vinkius delivers Streamable HTTP and SSE to any MCP client

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python

import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Domo "
            "(6 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Domo?"
    )
    print(result.data)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Domo MCP Server

Connect your Domo instance to any AI agent to streamline user administration and group management through natural language.

Pydantic AI validates every Domo tool response against typed schemas, catching data inconsistencies at build time. Connect 6 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

What you can do

User Administration — Create new users with specific roles (Admin, Privileged, Participant), update existing profiles, or remove users from the system.
Group Management — Create organizational groups to manage access at scale.
Membership Control — Seamlessly add or remove users from specific Domo groups to maintain security and collaboration standards.

The Domo MCP Server exposes 6 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — credentials fully managed, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 6 Domo tools available for Pydantic AI

When Pydantic AI connects to Domo through Vinkius, your AI agent gets direct access to every tool listed below — spanning user-administration, data-governance, analytics, and more. Every call runs in a secure, isolated environment with full audit visibility. Beyond a simple connection, you get real-time monitoring of agent activity, enterprise governance, and optimized token usage.

add

Add user to group on Domo

Add a user to a Domo group

create

Create group on Domo

Create a new Domo group

create

Create user on Domo

Optionally sends an invite email. Create a new Domo user

delete

Delete user on Domo

Delete a Domo user

remove

Remove user from group on Domo

Remove a user from a Domo group

update

Update user on Domo

Update an existing Domo user

Connect Domo to Pydantic AI via MCP

Follow these steps to wire Domo into Pydantic AI. The entire setup takes under two minutes — your credentials stay safe behind Vinkius.

Install Pydantic AI

Run pip install pydantic-ai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save to agent.py and run: python agent.py

Explore tools

The agent discovers 6 tools from Domo with type-safe schemas

Why Use Pydantic AI with the Domo MCP Server

Pydantic AI provides unique advantages when paired with Domo through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Domo integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Domo connection logic from agent behavior for testable, maintainable code

Domo + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Domo MCP Server delivers measurable value.

Type-safe data pipelines: query Domo with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Domo tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Domo and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Domo responses and write comprehensive agent tests

Example Prompts for Domo in Pydantic AI

Ready-to-use prompts you can give your Pydantic AI agent to start working with Domo immediately.

"Create a new Domo user for Alice Smith (alice@company.com) as a 'Privileged' user."

"Update user ID 55021 to have the job title 'Senior Analyst' and location 'New York'."

"Add user 10293 to the 'Data Science' group (ID 9982)."

Troubleshooting Domo MCP Server with Pydantic AI

Common issues when connecting Domo to Pydantic AI through Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Domo + Pydantic AI FAQ

Common questions about integrating Domo MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Domo MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.

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