How do I find my Teambition App ID and Secret?

Log in to the [Teambition Open Platform](https://open.teambition.com/), navigate to the 'Developer Center', and create a new application. Your App ID and App Secret will be generated there.

Can I assign tasks to specific team members?

Yes. When using `create_task` or `update_task`, you can provide an `executorId` to assign the task to a specific user. You can find user IDs using the `list_members` or `list_users` tools.

Does this server support Kanban stages?

Yes. You can use `list_task_groups` to see your project's lists and `list_stages` to see the specific columns (stages) within those groups, allowing you to track exactly where a task is in the workflow.

Teambition MCP Server for CrewAI 10 tools — connect in under 2 minutes

Name: Teambition
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 10 Tools Framework

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

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

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Vinkius supports streamable HTTP and SSE.

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="Teambition Specialist",
    goal="Help users interact with Teambition effectively",
    backstory=(
        "You are an expert at leveraging Teambition 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 Teambition "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 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 Teambition MCP Server

Empower your AI agent to orchestrate your team's productivity with Teambition, the leading collaboration platform under Alibaba Group. By connecting Teambition 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 organization members without you ever touching the web interface. Whether you are managing a software development sprint or a marketing campaign, your agent acts as a real-time project assistant, keeping your workspace organized and your team aligned.

When paired with CrewAI, Teambition becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Teambition 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 all accessible projects, get detailed info, and monitor overall progress.
Task Operations — Create, update, and track tasks with full support for descriptions, assignees, and due dates.
Workflow Visualization — Browse task groups and stages to understand your Kanban or list-based workflows.
Team Coordination — List project members and organization users to manage assignments effectively.
Organization Insights — Retrieve high-level information about your Teambition organization structure.

The Teambition MCP Server exposes 10 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 Teambition to CrewAI via MCP

Follow these steps to integrate the Teambition 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 10 tools from Teambition

Why Use CrewAI with the Teambition MCP Server

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

Teambition + CrewAI Use Cases

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

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

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

Teambition MCP Tools for CrewAI (10)

These 10 tools become available when you connect Teambition to CrewAI via MCP:

create_task

Create a new Teambition task

get_org_info

Get organization details

get_project

Get Teambition project details

list_members

List project members

list_projects

List all Teambition projects

list_stages

List stages in a task group

list_task_groups

List task groups in a project

list_tasks

List tasks in a project

list_users

List organization users

update_task

Update an existing Teambition task

Example Prompts for Teambition in CrewAI

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

"List all my active projects on Teambition."

"Create a task in project 'Product Launch' titled 'Review landing page copy'."

"Show me the tasks for project 'Internal Audit'."

Troubleshooting Teambition MCP Server with CrewAI

Common issues when connecting Teambition 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.

Teambition + CrewAI FAQ

Common questions about integrating Teambition 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.