Asana MCP Server for LlamaIndex 11 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Asana as an MCP tool provider through 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 Asana. "
"You have 11 tools available."
),
)
response = await agent.run(
"What tools are available in Asana?"
)
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 Asana MCP Server
Connect your Asana organizational account to any AI agent and take full control of your project management workflows through natural conversation.
LlamaIndex agents combine Asana tool responses with indexed documents for comprehensive, grounded answers. Connect 11 tools through 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
- Workspaces & Projects — List all organizational workspaces and fetch active projects directly from the Asana cloud
- Task Management — Query all recorded tasks (both pending and completed) from any target project using its unique GID
- Deep Task Inspection — Fetch complete metadata, descriptions, assignee fields, and precise status metrics for specific individual tasks
- Board Sections — List board column groupings and stages (sections) to categorize and understand sprint workflows
- User Profiling — Retrieve the underlying credentials, profile information, and authorized access of your agent's API user
The Asana MCP Server exposes 11 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 Asana to LlamaIndex via MCP
Follow these steps to integrate the Asana 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 11 tools from Asana
Why Use LlamaIndex with the Asana MCP Server
LlamaIndex provides unique advantages when paired with Asana through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Asana tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Asana tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Asana, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Asana tools were called, what data was returned, and how it influenced the final answer
Asana + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Asana MCP Server delivers measurable value.
Hybrid search: combine Asana real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Asana 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 Asana for fresh data
Analytical workflows: chain Asana queries with LlamaIndex's data connectors to build multi-source analytical reports
Asana MCP Tools for LlamaIndex (11)
These 11 tools become available when you connect Asana to LlamaIndex via MCP:
create_task
Create a new Asana task
get_me
Get current Asana user details
get_task
Get details for a specific Asana task
list_projects
List projects in a workspace
list_sections
List sections inside an Asana project
list_stories
List activity feed (stories) for a task
list_tags
List all tags in a workspace
list_tasks
List tasks in an Asana project
list_workspaces
List Asana workspaces
search_tasks
Search for tasks in a workspace with filters
update_task
Update an existing Asana task
Example Prompts for Asana in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with Asana immediately.
"List all our active organizational workspaces on Asana."
"Can you fetch the tasks pending inside project 1205934?"
"Provide the complete details and assignee for task GID 12039402123."
Troubleshooting Asana MCP Server with LlamaIndex
Common issues when connecting Asana to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpAsana + LlamaIndex FAQ
Common questions about integrating Asana 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?
Connect Asana with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Asana to LlamaIndex
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.