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Basecamp MCP Server for Pydantic AIGive Pydantic AI instant access to 17 tools to Complete Todo, Create Comment, Create Project, and more

Built by Vinkius GDPR 17 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Basecamp 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 Basecamp app connector for Pydantic AI is a standout in the Productivity category — giving your AI agent 17 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 Basecamp "
            "(17 tools)."
        ),
    )

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

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

Connect your Basecamp account to any AI agent and take full control of your project management, team collaboration, and task tracking through natural conversation.

Pydantic AI validates every Basecamp tool response against typed schemas, catching data inconsistencies at build time. Connect 17 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 Management — Create, list, update, and inspect projects with full dock metadata (message boards, to-do sets, schedules).
  • To-Do CRUD — Create, update, complete, and uncomplete to-do items across any to-do list, with assignees and due dates.
  • Team Visibility — List all people in your account or within a specific project to find assignee IDs and check roles.
  • Message Boards — Read messages posted on project boards to stay aligned with team decisions and announcements.
  • Comments — Add comments to any recording (to-do, message, document) to provide feedback or status updates.
  • Profile Verification — Retrieve your authenticated profile to confirm connectivity and check access permissions.

The Basecamp MCP Server exposes 17 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 17 Basecamp tools available for Pydantic AI

When Pydantic AI connects to Basecamp through Vinkius, your AI agent gets direct access to every tool listed below — spanning task-tracking, team-communication, file-sharing, 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.

complete_todo

This is separate from archiving or trashing — a completed to-do remains active but is marked as done. Use uncomplete_todo to reverse this action. Mark a to-do item as completed

create_comment

). The recording_id is the unique numeric ID of the item you want to comment on. The content must be provided as rich text (HTML). All subscribers to the recording will be notified of the new comment. Add a comment to any Basecamp recording

create_project

The project will be initialized with default tools (message board, to-do set, schedule, etc.) enabled via its dock. Returns the newly created project with its numeric ID and dock tool IDs. Create a new project in Basecamp

create_todo

Requires the todolist_id and the content (title) of the to-do. Optionally include a rich text description, assignee IDs (array of person IDs), and a due date in YYYY-MM-DD format. The to-do will be created as pending (not completed). Create a new to-do item in a to-do list

get_message

Get full details of a specific message

get_my_profile

Use this to verify connectivity or identify the current operator. Get the authenticated Basecamp user profile

get_person

Use this to look up details about a team member or assignee. Get full details of a specific person

get_project

). The dock contains the IDs you need to access tools like the to-do set or message board. Get full details of a specific project

get_todo

Get full details of a specific to-do item

list_messages

Each message includes title, content preview, author, category, and creation date. You need the message_board_id which can be found via the project dock. List all messages on a project message board

list_people

Useful for finding assignee IDs before creating or updating to-dos. List all people in the Basecamp account

list_project_people

Returns names, emails, and roles. Useful for checking team composition before assigning tasks. List all people assigned to a specific project

list_projects

Optionally filter by status: "active" (default), "archived", or "trashed". Each project includes its name, description, purpose, dock (enabled tools), and bookmark status. List all projects in Basecamp

list_todos

By default returns only pending (not completed) items. Set completed to true to see completed items instead. Each to-do includes its content, assignees, due date, completion status, and comments count. You need the todolist_id which can be found via the project dock. List all to-dos in a specific to-do list

uncomplete_todo

Use this when a previously completed task needs to be reopened or reworked. Mark a completed to-do item as pending again

update_project

At least one of name or description must be provided. Returns the updated project details including the full dock listing. Update an existing project in Basecamp

update_todo

At least one field must be provided. Does not affect completion status — use the complete_todo or uncomplete_todo tools for that. Update an existing to-do item in Basecamp

Connect Basecamp to Pydantic AI via MCP

Follow these steps to wire Basecamp 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 17 tools from Basecamp with type-safe schemas

Why Use Pydantic AI with the Basecamp MCP Server

Pydantic AI provides unique advantages when paired with Basecamp 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 Basecamp 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 Basecamp connection logic from agent behavior for testable, maintainable code

Basecamp + Pydantic AI Use Cases

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

01

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

02

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

03

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

04

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

Example Prompts for Basecamp in Pydantic AI

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

01

"List all my active projects in Basecamp."

02

"Create a new to-do 'Review design mockups' in list 592001 and assign it to person 10293 with a due date of 2026-05-15."

03

"Show me the latest messages on the message board of project 48291034."

Troubleshooting Basecamp MCP Server with Pydantic AI

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

01

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Basecamp + Pydantic AI FAQ

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