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 LangChain 17 tools — connect in under 2 minutes

Name: Teamwork Projects
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 17 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Teamwork Projects through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

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 langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "teamwork-projects": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Teamwork Projects, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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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 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.

LangChain's ecosystem of 500+ components combines seamlessly with Teamwork Projects through native MCP adapters. Connect 17 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

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

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 17 tools from Teamwork Projects via MCP

Why Use LangChain with the Teamwork Projects MCP Server

LangChain provides unique advantages when paired with Teamwork Projects through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Teamwork Projects MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Teamwork Projects queries for multi-turn workflows

Teamwork Projects + LangChain Use Cases

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

RAG with live data: combine Teamwork Projects tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Teamwork Projects, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Teamwork Projects tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Teamwork Projects tool call, measure latency, and optimize your agent's performance

Teamwork Projects MCP Tools for LangChain (17)

These 17 tools become available when you connect Teamwork Projects to LangChain 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 LangChain

Ready-to-use prompts you can give your LangChain 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 LangChain

Common issues when connecting Teamwork Projects to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Teamwork Projects + LangChain FAQ

Common questions about integrating Teamwork Projects MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.