How do I connect my account?

Subscribe and provide two things: your **ProofHub Domain** (the 'mycompany' part of `mycompany.proofhub.com`) and your **API Key**. The API Key is somewhat hidden: log into ProofHub, click your profile picture in the bottom-left corner 5 times straight to reveal the 'API access' option, then generate or copy your key.

Can my agent create tasks directly?

Yes! Just tell your agent the project name (or ID), the to-do list, and the title of the task you want created. It will use the `create_task` tool to instantly drop that work item into the specified ProofHub list for your team to pick up.

How can I see what the team has been discussing?

Ask your agent to 'list discussions for project X'. It retrieves all recent discussion topics securely, allowing you to stay in the loop on project blockers, decisions, and brainstorming without opening multiple communication tabs.

Can this server pull files and notes?

Yes. Beyond tasks, the agent can query both `list_files` and `list_notes` for any given project ID. If someone uploaded project requirements or drafted meeting notes, your AI assistant can surface their metadata and context on demand.

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

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

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

Connect your ProofHub domain to any AI agent to streamline project management and team collaboration directly from your workflow.

Pydantic AI validates every ProofHub 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

Project Overviews — Retrieve all active projects, detailed metadata, and overarching status instantly
Task & To-do Management — Fetch to-do lists, see assigned tasks, and even create new work items on the fly
Team Collaboration — Read project discussions, track newly uploaded files, and access shared notebooks and documentation
Resource Management — List all team members, check active statuses, and audit logged hours and productivity via timesheets

The ProofHub 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 ProofHub to Pydantic AI via MCP

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

Why Use Pydantic AI with the ProofHub MCP Server

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

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

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

ProofHub + Pydantic AI Use Cases

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

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

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

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

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

ProofHub MCP Tools for Pydantic AI (10)

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

create_task

You must provide a valid project ID and todolist ID. Creates a new task in a ProofHub to-do list

get_project

Retrieves full details of a ProofHub project

list_discussions

Lists all discussions (topics) in a ProofHub project

list_files

Lists all files uploaded to a ProofHub project

list_notes

Lists all notes/notebooks in a ProofHub project

list_people

Lists all team members in ProofHub

list_projects

ProofHub is a collaboration tool with tasks, discussions, and files. Lists all projects in ProofHub

list_tasks

Lists all tasks in a ProofHub to-do list

list_timesheets

Lists all timesheet entries for a project

list_todolists

Use this to find the correct list ID before querying or creating tasks. Lists all to-do lists within a ProofHub project

Example Prompts for ProofHub in Pydantic AI

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

"List all active projects on ProofHub right now."

"Check the to-do list for 'Website Overhaul' and show what's pending."

"Create a task in project 105 (todolist 201) to 'Test checkout flow'."

Troubleshooting ProofHub MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

ProofHub + Pydantic AI FAQ

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