How do I find my Metaplane API Key?

Log in to Metaplane, go to your Account Settings, and you can generate or copy your API Key from the API section.

Can I trigger a monitor run manually?

Yes! Use the `trigger_monitor_run` tool and provide the monitor ID to start a data quality check immediately.

Is my data observability data secure?

Absolutely. Your token is encrypted at rest and injected securely at runtime.

Metaplane MCP Server for Pydantic AI 10 tools — connect in under 2 minutes

Name: Metaplane
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 10 Tools SDK

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

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 Metaplane "
            "(10 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Metaplane?"
    )
    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 Metaplane MCP Server

Connect your Metaplane account to any AI agent and take full control of your data observability and quality through natural conversation.

Pydantic AI validates every Metaplane tool response against typed schemas, catching data inconsistencies at build time. Connect 10 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

Monitor Oversight — List all configured data monitors and fetch detailed metadata and health statuses
Incident Management — Retrieve real-time incident histories and track resolutions for data quality alerts
Automated Execution — Programmatically trigger monitor runs to validate data quality on demand
Connection Visibility — Enumerate connected databases, warehouses, and schemas to understand your data lineage
Alert Configuration — List and inspect active notification settings and alert rules

The Metaplane MCP Server exposes 10 tools through the Vinkius. Connect it to Pydantic AI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Metaplane to Pydantic AI via MCP

Follow these steps to integrate the Metaplane MCP Server with Pydantic AI.

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 10 tools from Metaplane with type-safe schemas

Why Use Pydantic AI with the Metaplane MCP Server

Pydantic AI provides unique advantages when paired with Metaplane 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 Metaplane integration code

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

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

Metaplane + Pydantic AI Use Cases

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

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

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

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

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

Metaplane MCP Tools for Pydantic AI (10)

These 10 tools become available when you connect Metaplane to Pydantic AI via MCP:

get_account_info

Get account information

get_incident

Get details for a specific incident

get_monitor

Get details for a specific monitor

get_monitor_runs

Get run history for a monitor

list_configured_alerts

List configured alerts

list_connection_schemas

List schemas for a connection

list_data_connections

List all data source connections

list_incidents

List data incidents

list_monitors

List all data monitors

trigger_monitor_run

Trigger a monitor run

Example Prompts for Metaplane in Pydantic AI

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

"List all my data monitors in Metaplane."

"Show recent incidents for the last 24 hours."

"Trigger a run for monitor ID 'mon_12345'."

Troubleshooting Metaplane MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Metaplane + Pydantic AI FAQ

Common questions about integrating Metaplane 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 Metaplane MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.