How do I find my Planhat API Token?

In your Planhat account, go to **Settings** > **API**. There you can generate and copy your security token.

Can I see all end users for a specific company?

Yes! Use the `list_planhat_end_users` tool. You can then ask the AI agent to filter the results for a particular company name or ID from the retrieved list.

Does this support checking active licenses?

Absolutely. Use the `list_planhat_licenses` tool to retrieve a comprehensive list of all customer licenses and their associated data.

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

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

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

Connect your Planhat workspace to any AI agent and take full control of your customer success and growth workflows through natural conversation.

Pydantic AI validates every Planhat 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

Company Oversight — List all companies and retrieve detailed metadata to manage your customer relationships.
User & Contact Tracking — List end users and associated metadata to understand your user base.
Task & Activity Management — List pending tasks and monitor activities to ensure proactive customer management.
Conversation Discovery — List all ongoing conversations to maintain a pulse on customer communication.
License & Asset Auditing — List configured licenses and assets to verify customer entitlements.
Project Monitoring — List active projects to track implementation and success plans.

The Planhat 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 Planhat to Pydantic AI via MCP

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

Why Use Pydantic AI with the Planhat MCP Server

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

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

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

Planhat + Pydantic AI Use Cases

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

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

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

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

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

Planhat MCP Tools for Pydantic AI (10)

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

get_planhat_company

Get details for a specific company

get_planhat_me

Get current user info

list_planhat_assets

List all assets

list_planhat_companies

List all companies in Planhat

list_planhat_conversations

List all conversations

list_planhat_end_users

List all end users

list_planhat_licenses

List all licenses

list_planhat_notes

List all notes

list_planhat_projects

List all projects

list_planhat_tasks

List all tasks

Example Prompts for Planhat in Pydantic AI

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

"List all active companies in my Planhat account."

"Show me the last 5 tasks assigned to me in Planhat."

"What are the active licenses for company 'Acme Corp'?"

Troubleshooting Planhat MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Planhat + Pydantic AI FAQ

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