How do I obtain a Tower Access Token?

Log in to your Tower account, go to the [App Center](https://tower.im/oauth/tokens), and generate a new Personal Access Token. Make sure to copy it immediately.

Can I see team discussions through this server?

Yes. Use the `list_discussions` tool with a project ID to retrieve the list of recent topics and discussions shared within that project.

Is it possible to manage multiple teams?

Yes. You can use `list_teams` to see all teams you are a part of and then use the team IDs to list members or access specific projects associated with those teams.

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

Name: Tower
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 Tower through the 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 Tower "
            "(10 tools)."
        ),
    )

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

asyncio.run(main())

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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 Tower MCP Server

Empower your AI agent to orchestrate your team's productivity with Tower, the lightweight and intuitive collaboration platform. By connecting Tower to your agent, you transform complex project tracking and task assignment into a natural conversation. Your agent can instantly list your projects, create new tasks, update statuses, and even browse project discussions without you ever needing to navigate the web interface. Whether you are managing a small creative project or a large-scale operation, your agent acts as a real-time team assistant, keeping your workspace organized and your team aligned.

Pydantic AI validates every Tower tool response against typed schemas, catching data inconsistencies at build time. Connect 10 tools through the 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 Management — List all accessible projects and retrieve detailed information about your collaboration workspace.
Task Operations — Create, update, and track tasks with full support for descriptions, assignees, and completion status.
Team Coordination — List teams and members to manage assignments and collaboration effectively.
Discussion Monitoring — Browse project discussions and topics to stay informed about team updates.
Resource Organization — List document folders within projects to access shared resources instantly.

The Tower 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 Tower to Pydantic AI via MCP

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

Why Use Pydantic AI with the Tower MCP Server

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

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

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

Tower + Pydantic AI Use Cases

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

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

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

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

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

Tower MCP Tools for Pydantic AI (10)

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

create_task

Create a new Tower task

get_project

Get project details

get_task_details

Get task details

list_discussions

List project discussions

list_doc_folders

List document folders

list_members

List team members

list_projects

List all Tower projects

list_tasks

List tasks in a project

list_teams

List available teams

update_task

Update an existing Tower task

Example Prompts for Tower in Pydantic AI

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

"List all my active projects on Tower."

"Create a task in project 'Design Refresh' titled 'Select primary color palette'."

"Show me recent discussions in the 'API Integration' project."

Troubleshooting Tower MCP Server with Pydantic AI

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

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Tower + Pydantic AI FAQ

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