Teamwork Projects MCP Server for LlamaIndex 17 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Teamwork Projects as an MCP tool provider through the Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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Vinkius supports streamable HTTP and SSE.
import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token — get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to Teamwork Projects. "
"You have 17 tools available."
),
)
response = await agent.run(
"What tools are available in Teamwork Projects?"
)
print(response)
asyncio.run(main())
* 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.
LlamaIndex agents combine Teamwork Projects tool responses with indexed documents for comprehensive, grounded answers. Connect 17 tools through the Vinkius and query live data alongside vector stores and SQL databases in a single turn — ideal for hybrid search, data enrichment, and analytical workflows.
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 LlamaIndex 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 LlamaIndex via MCP
Follow these steps to integrate the Teamwork Projects MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 17 tools from Teamwork Projects
Why Use LlamaIndex with the Teamwork Projects MCP Server
LlamaIndex provides unique advantages when paired with Teamwork Projects through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Teamwork Projects tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Teamwork Projects tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Teamwork Projects, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Teamwork Projects tools were called, what data was returned, and how it influenced the final answer
Teamwork Projects + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Teamwork Projects MCP Server delivers measurable value.
Hybrid search: combine Teamwork Projects real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Teamwork Projects to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying Teamwork Projects for fresh data
Analytical workflows: chain Teamwork Projects queries with LlamaIndex's data connectors to build multi-source analytical reports
Teamwork Projects MCP Tools for LlamaIndex (17)
These 17 tools become available when you connect Teamwork Projects to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Teamwork Projects to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTeamwork Projects + LlamaIndex FAQ
Common questions about integrating Teamwork Projects MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
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Connect Teamwork Projects to LlamaIndex
Get your token, paste the configuration, and start using 17 tools in under 2 minutes. No API key management needed.