How do I get Innform API credentials?

You can generate an API key in your Innform account under Account Settings > API. Ensure you have the necessary permissions.

Can I see learner results?

Yes, the list_results tool provides access to assessment and course completion data for your learners.

Are learning pathways supported?

Yes, you can list all defined learning pathways using the list_pathways tool.

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

Name: Innform
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 Innform 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 Innform "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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* 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 Innform MCP Server

Empower your AI agents to manage your training platform with Innform. This MCP server allows you to list learners, track course completion, manage learning pathways, and view results directly through the Innform API. Ideal for automating corporate training and employee development.

Pydantic AI validates every Innform 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.

The Innform 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 Innform to Pydantic AI via MCP

Follow these steps to integrate the Innform 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 Innform with type-safe schemas

Why Use Pydantic AI with the Innform MCP Server

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

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

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

Innform + Pydantic AI Use Cases

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

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

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

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

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

Innform MCP Tools for Pydantic AI (10)

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

get_learner

Retrieves details for a specific learner

get_me

Gets current authenticated user info

list_courses

Lists all courses

list_departments

Lists all departments

list_learners

Lists all learners in Innform

list_locations

Lists all organization locations

list_modules

Lists all training modules

list_pathways

Lists all learning pathways

list_results

Lists learner assessment and course results

list_tags

Lists all defined tags

Example Prompts for Innform in Pydantic AI

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

"List all active learners in my Innform account."

"Show me the results for 'Cybersecurity Awareness' course."

"Check for any new learning pathways."

Troubleshooting Innform MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Innform + Pydantic AI FAQ

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