Can I create a to-do and assign it to a team member directly via the AI agent?

Yes! Use the `create_todo` tool with the to-do list ID, content, and the assignee person IDs. You can also set a due date. The to-do will be created and assigned instantly in Basecamp.

How do I find the to-do list ID I need to create tasks in?

First, use `get_project` to retrieve the project details — the dock will contain the `todoset` ID. Then use the Basecamp UI or the to-do set to find your specific to-do list IDs within that project.

Can I mark a to-do as completed and later reopen it if needed?

Absolutely. Use the `complete_todo` tool to mark a to-do as done, and `uncomplete_todo` to reopen it. This only affects the completion status — the to-do remains active and visible in the project.

INSTANT PLUG AND PLAY

Basecamp MCP Server for CrewAIGive CrewAI instant access to 17 tools to Complete Todo, Create Comment, Create Project, and more

Name: Basecamp
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 17 Tools Framework

Connect your CrewAI agents to Basecamp through Vinkius, pass the Edge URL in the `mcps` parameter and every Basecamp tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The Basecamp app connector for CrewAI 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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Basecamp Specialist",
    goal="Help users interact with Basecamp effectively",
    backstory=(
        "You are an expert at leveraging Basecamp tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Basecamp "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 17 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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 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.

When paired with CrewAI, Basecamp becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Basecamp tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI

When CrewAI 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 CrewAI via MCP

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

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 17 tools from Basecamp

Why Use CrewAI with the Basecamp MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Basecamp through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Basecamp + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Basecamp for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Basecamp, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Basecamp tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Basecamp against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for Basecamp in CrewAI

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

"List all my active projects in Basecamp."

"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."

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

Troubleshooting Basecamp MCP Server with CrewAI

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

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Basecamp + CrewAI FAQ

Common questions about integrating Basecamp MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.