How do I get my Teamwork Access Token?

Log in to Teamwork, go to your Profile picture > My Profile > Developer, and generate a Personal Access Token.

Can I create tasks with assignees?

Yes! Use the create_task action with a JSON body that includes content, tasklist_id, and responsible-party-ids for assignment.

Can I log time against a project?

Yes! Use the create_time_entry action with a JSON body that includes description, duration (in minutes or seconds), and date.

Can I retrieve project milestones?

Yes! Use the list_milestones action to get all project milestones and their deadlines.

Teamwork Projects MCP Server for CrewAI 17 tools — connect in under 2 minutes

Name: Teamwork Projects
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 17 Tools Framework

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

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python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Teamwork Projects Specialist",
    goal="Help users interact with Teamwork Projects effectively",
    backstory=(
        "You are an expert at leveraging Teamwork Projects 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 Teamwork Projects "
        "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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About Teamwork Projects MCP Server

Connect Teamwork to any AI agent and manage your project delivery platform — create and track tasks, manage milestones, log time, post messages, and monitor project progress through natural conversation.

When paired with CrewAI, Teamwork Projects becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Teamwork Projects 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 — List and create projects for organizing work
Task Management — Create, update, and delete tasks with assignees and due dates
Milestones — Track project milestones and deadlines
Time Tracking — Log and review time entries against projects
Messages — Post announcements and discussions in projects
Files — List and access project files and attachments

The Teamwork Projects 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.

How to Connect Teamwork Projects to CrewAI via MCP

Follow these steps to integrate the Teamwork Projects MCP Server with CrewAI.

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 Teamwork Projects

Why Use CrewAI with the Teamwork Projects MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Teamwork Projects 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

Teamwork Projects + CrewAI Use Cases

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

Automated multi-step research: a reconnaissance agent queries Teamwork Projects 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 Teamwork Projects, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Teamwork Projects 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 Teamwork Projects against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Teamwork Projects MCP Tools for CrewAI (17)

These 17 tools become available when you connect Teamwork Projects to CrewAI via MCP:

create_message

Body should include title and body content. Post a new message in a project

create_milestone

Body should include title and deadline date. Create a new milestone in a project

create_project

Body should include name and optional settings. Create a new project

create_task

Body should include content, tasklist_id, assignee_ids, and due dates. Create a new task

create_time_entry

Body should include description, duration, and date. Log a new time entry

delete_task

Delete a task

get_current_user

Use this to verify connection and identify your user ID. Get the authenticated user profile

get_project

Get details of a specific project

get_task

Get details of a specific task

list_files

List all files in a project

list_messages

List all messages in a project

list_milestones

List all milestones in a project

list_projects

Use project IDs to query tasks, milestones, and other resources within specific projects. List all projects accessible to the user

list_tasklists

Use task list IDs to query specific tasks. List all task lists in a project

list_tasks

List all tasks in a project

list_time_entries

List all time entries in a project

update_task

Update an existing task

Example Prompts for Teamwork Projects in CrewAI

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

"Show me all my projects."

"List all tasks in project 12345."

"Create a milestone 'Phase 1 Complete' with deadline 2025-05-01 in project 12345."

Troubleshooting Teamwork Projects MCP Server with CrewAI

Common issues when connecting Teamwork Projects 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.

Teamwork Projects + CrewAI FAQ

Common questions about integrating Teamwork Projects 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.