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TeamGantt MCP Server for Pydantic AIGive Pydantic AI instant access to 12 tools to Create New Task, Get Account Profile, Get Project Details, and more

Built by Vinkius GDPR 12 Tools SDK

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

Ask AI about this App Connector for Pydantic AI

The TeamGantt app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 12 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

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 TeamGantt "
            "(12 tools)."
        ),
    )

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

asyncio.run(main())
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About TeamGantt MCP Server

Connect your TeamGantt account to any AI agent and simplify how you manage your project timelines, task assignments, and team resources through natural conversation.

Pydantic AI validates every TeamGantt tool response against typed schemas, catching data inconsistencies at build time. Connect 12 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

  • Project Oversight — List all projects in your account and retrieve detailed metadata and configuration for specific Gantt charts.
  • Task Management — Create, update, and delete tasks with full control over start/end dates and completion percentages.
  • Timeline Coordination — Create dependencies between tasks to ensure your project logic remains sound and automated.
  • Resource Tracking — List available resources (people and equipment) to optimize team allocation across projects.
  • Milestone Planning — List and query major project goals (milestones) and sub-task checklists.
  • Account Visibility — Fetch your user profile and verify account configurations directly from the agent.

The TeamGantt MCP Server exposes 12 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.

All 12 TeamGantt tools available for Pydantic AI

When Pydantic AI connects to TeamGantt through Vinkius, your AI agent gets direct access to every tool listed below — spanning gantt-charts, project-planning, task-management, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.

create_new_task

Add task to project

get_account_profile

Get user info

get_project_details

Get project info

get_task_checklist

List sub-tasks

get_task_info

Get task details

link_tasks_dependency

g. Task A must finish before Task B starts). Create Gantt link

list_available_resources

List users and labels

list_project_milestones

List major goals

list_project_tasks

List tasks in project

list_projects

List TeamGantt projects

remove_task

Delete task

update_task_fields

). Update task status/dates

Connect TeamGantt to Pydantic AI via MCP

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

01

Install Pydantic AI

Run pip install pydantic-ai
02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token
03

Run the agent

Save to agent.py and run: python agent.py
04

Explore tools

The agent discovers 12 tools from TeamGantt with type-safe schemas

Why Use Pydantic AI with the TeamGantt MCP Server

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

01

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

02

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

03

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

04

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

TeamGantt + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for TeamGantt in Pydantic AI

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

01

"List all active projects in my TeamGantt account."

02

"Show me the tasks for 'Website Launch Q4' (ID: 10293)."

03

"Mark task '88231' as 100% complete."

Troubleshooting TeamGantt MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

TeamGantt + Pydantic AI FAQ

Common questions about integrating TeamGantt MCP Server with Pydantic AI.

01

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.
02

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.
03

Can I switch LLM providers without changing MCP code?

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