Can my AI automatically find the details and status of a specific task just by providing the Task GID?

Yes! Use the `get_task` tool with exactly the Task Global ID. Your agent will respond with complete metadata, assignee fields, and precise operational notes connected to that active ticket in seconds.

How do I easily list all the columns in an active agile sprint board?

Simply ask the agent to run the `list_sections` action on the target Project GID. It will compile all column phases (e.g., 'To Do', 'In Progress', 'QA') configured for that environment.

Does the integration permit modifying or deleting my workspace configurations?

No. The core set of tools focuses strictly on heavily querying and analyzing context—listing projects, analyzing metadata, checking tasks. State alteration operations are not currently exposed, assuring your workspaces are secure against destructive queries.

Asana MCP Server for Pydantic AI 11 tools — connect in under 2 minutes

Name: Asana
Availability: InStock
Author: Vinkius

ai.pydantic.dev/mcp

Built by Vinkius GDPR 11 Tools SDK

Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Asana through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.

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 pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")

    agent = Agent(
        model="openai:gpt-4o",
        mcp_servers=[server],
        system_prompt=(
            "You are an assistant with access to Asana "
            "(11 tools)."
        ),
    )

    result = await agent.run(
        "What tools are available in Asana?"
    )
    print(result.data)

asyncio.run(main())

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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

Pydantic AI validates every Asana tool response against typed schemas, catching data inconsistencies at build time. Connect 11 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.

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 Pydantic AI 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 Pydantic AI via MCP

Follow these steps to integrate the Asana MCP Server with Pydantic AI.

Install Pydantic AI

Run pip install pydantic-ai

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 with type-safe schemas

Why Use Pydantic AI with the Asana MCP Server

Pydantic AI provides unique advantages when paired with Asana through the Model Context Protocol.

Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application

Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Asana integration code

Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors

Dependency injection system cleanly separates your Asana connection logic from agent behavior for testable, maintainable code

Asana + Pydantic AI Use Cases

Practical scenarios where Pydantic AI combined with the Asana MCP Server delivers measurable value.

Type-safe data pipelines: query Asana with guaranteed response schemas, feeding validated data into downstream processing

API orchestration: chain multiple Asana tool calls with Pydantic validation at each step to ensure data integrity end-to-end

Production monitoring: build validated alert agents that query Asana and output structured, schema-compliant notifications

Testing and QA: use Pydantic AI's dependency injection to mock Asana responses and write comprehensive agent tests

Asana MCP Tools for Pydantic AI (11)

These 11 tools become available when you connect Asana to Pydantic AI 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 Pydantic AI

Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI

Common issues when connecting Asana to Pydantic AI through the Vinkius, and how to resolve them.

MCPServerHTTP not found

Update: pip install --upgrade pydantic-ai

Asana + Pydantic AI FAQ

Common questions about integrating Asana MCP Server with Pydantic AI.

How does Pydantic AI discover MCP tools?

Create an MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.

Does Pydantic AI validate MCP tool responses?

Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.

Can I switch LLM providers without changing MCP code?

Absolutely. Pydantic AI abstracts the model layer. your Asana MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.