asana · MCP Server

Connect Asana to AI with Improvado MCP

Improvado's MCP server connects Asana to Claude, Cursor, and other AI agents. Query your Asana data in natural language — no manual exports or API scripts required.

46K+ metrics ·Read & Write access ·500+ platforms ·<60s setup

Read

Read: Instant Answers from Asana

Stop digging through projects and portfolios manually. Ask your AI agent to surface blocked tasks, overdue milestones, workload imbalances, and cross-team dependencies — across every workspace you own.

Example prompts

"Which tasks across all active projects are overdue by more than 7 days and still unassigned?"

25 min → 30 sec

"Show me every task assigned to the onboarding team that's blocked or waiting on external input right now."

20 min → 45 sec

"Summarize the current sprint status for the product launch project: what's done, what's at risk, and what's not started."

30 min → 1 min

Works with Claude ChatGPT Cursor +5

Write

Write: Automate Asana Updates

Skip the manual task creation and status updates. Your AI agent can create tasks from meeting notes, reassign blocked work, update due dates, and move items through workflows — without opening Asana.

Example prompts

"Create tasks in the Q2 onboarding project for each action item from this meeting transcript, assign to the relevant owner."

20 min → 1 min

"Reassign all tasks currently assigned to [departing team member] to [new owner] and flag the project manager."

30 min → 30 sec

"Move all tasks marked 'ready for review' in the content pipeline project to the 'In Review' section."

15 min → 20 sec

Every action logged · Fully reversible · SOC 2 certified

Monitor

Monitor: Catch Asana Blockers Before They Slip

Set AI-powered watches on project health, deadline risk, and workload distribution. Get proactive alerts when milestones are at risk, team members are overloaded, or dependencies are unresolved.

Example prompts

"Alert me every Monday morning if any project milestone is at risk of missing its due date this week."

Manual → auto

"Every Friday: send a summary of completed tasks, blocked items, and the top 3 risks across all active portfolios."

2 hrs → auto

"Flag any team member whose assigned task count exceeds 15 open items, and suggest rebalancing options."

Manual → auto

Alerts sent to Slack, email, or your AI agent

Full cycle

The Closed Loop: Read → Decide → Write → Monitor

Your AI agent doesn't just surface data — it acts. Adjust pricing, update product descriptions, manage inventory, apply discounts — all through natural language. The MCP server translates intent into API operations.

Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.

Ideate

Launch

Measure

Analyze

Report

Iterate

One conversation. All six phases. Every platform.

The daily grind

Common problems. Direct answers.

Challenge 1

Onboarding Friction Across Systems

The problem

New team members and partner teams often struggle to get context from Asana boards — especially when onboarding involves multiple systems. Getting up to speed means reading through dozens of tasks, comments, and project histories, which takes days instead of hours.

How MCP solves it

Ask your AI agent to summarize the current state of any Asana project, extract open action items, and identify who owns what. The agent synthesizes weeks of task history into a two-minute briefing.

Try asking

Summarize the current status of the Acme Corp onboarding project: what's been completed, what's open, and who is responsible for each open item.

Answer in seconds

All data sources, one query

Challenge 2

Fragmented Tooling Creates Visibility Gaps

The problem

Teams using Asana alongside Notion, Confluence, and other project tools end up with work scattered across platforms. Getting a unified view of project status means manually checking each tool — leading to missed dependencies and duplicated effort.

How MCP solves it

Improvado MCP connects Asana to your AI agent alongside other tools. Ask a single question that spans Asana tasks and linked context from other sources. One prompt surfaces the full picture without platform-hopping.

Try asking

Show me all Asana tasks tagged as 'blocked' across every active project, and tell me what information or decisions each one is waiting on.

Full detail preserved

No data loss on export

Challenge 3

Reporting on Project Health Takes Too Long

The problem

Preparing weekly project status reports from Asana requires manually reviewing each project, checking task statuses, calculating completion rates, and identifying risks. For teams running 10+ simultaneous projects, this alone consumes hours every week.

How MCP solves it

One prompt generates a complete portfolio health report. Your AI agent queries all active projects, calculates on-track vs at-risk rates, surfaces top blockers, and formats the output for a leadership summary in under a minute.

Try asking

Generate a portfolio health report for this week: overall completion rate, projects at risk, and the top 3 blockers holding up delivery across all teams.

Unified data model

Compare anything side by side

👥 Teams

One Framework. Five Roles. Zero Setup.

Same MCP connection, different workflows for every team member. Each role asks in natural language — the MCP server handles the complexity (rate limits, auth, schema normalization, governance) behind the scenes.

Agency CEO

Portfolio health. Client risk. Revenue signals.

Media Strategist

70% strategy, not 70% ops. Auto campaign QA.

Marketing Analyst

Zero wrangling. Cross-platform. AI narratives.

Account Manager

QBR decks auto-generated. Call prep in 30s.

Creative Director

Performance-to-brief. Predict winners before spend.

FAQ

Common questions

What is Asana MCP?

Asana MCP is a Model Context Protocol server that connects your Asana workspace data to AI agents like Claude, ChatGPT, and Gemini. It lets you query tasks, projects, portfolios, and team workloads in natural language — without logging into Asana or building integrations — all through Improvado's hosted MCP server.

Which Asana data can I access through the MCP server?

Tasks, subtasks, projects, portfolios, sections, assignees, due dates, custom fields, comments, attachments, dependencies, and workspace members. Everything accessible via Asana's REST API is queryable through your AI agent.

Can the AI agent create and update tasks or only read data?

Both. Read operations cover querying tasks, project statuses, and workload data. Write operations include creating tasks, updating statuses and due dates, reassigning work, adding comments, and moving tasks between sections. Permission scope is controlled by your Asana API token.

Does this work across multiple Asana workspaces and portfolios?

Yes. Improvado's MCP server handles multi-workspace queries. You can ask a single question that spans all your Asana portfolios and projects simultaneously — no need to switch between workspaces or run separate queries.

Is my Asana data secure through the MCP server?

Yes. Improvado stores all API credentials in an encrypted vault certified to SOC 2 Type II. Your AI agent never has direct access to credentials — requests go through Improvado's secure proxy. Prompt injection protection is built in.

How quickly can I set this up?

Under 60 seconds for Claude Desktop or Cursor users. Add the MCP server URL to your config, authenticate with an Asana personal access token, and you're querying. Improvado users already connected to Asana can start immediately via app.improvado.io/agent.

Stop Reporting. Start Executing.

Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.

SOC 2 Type II GDPR 500+ Platforms