Asana
Free foreverasana · Productivity
18k installs
The Asana MCP server connects your Asana workspace directly to any AI agent through a single hosted Model Context Protocol endpoint, letting Claude, GPT, Gemini, or any MCP-compatible assistant read and write tasks, projects, and status updates without custom API glue code. Instead of building and maintaining a bespoke Asana integration for every AI tool your team adopts, you connect Asana once through BusinessMCP.com and expose it everywhere via /api/mcp with a Bearer mcph_* key — making this a practical Asana MCP server for teams standardizing on agent-driven work management rather than juggling one-off scripts.
Once connected, an agent can create tasks and subtasks, assign owners, set due dates, update project status, move items across sections, add comments, and pull progress reports on demand — all grounded in your live Asana data rather than a stale export. This makes it well suited for teams who want an AI assistant that can triage a backlog, summarize what's overdue across projects, or turn a meeting transcript into properly assigned tasks without a human re-typing everything into Asana by hand. Because the server is model-agnostic, the same connection works whether your team standardizes on Claude for planning, GPT for drafting task descriptions, or Gemini for status digests — no re-integration required when you switch or mix models.
What sets this apart from a point-to-point Asana integration is that it lives inside BusinessMCP's unified hosted MCP server and business-intelligence layer. Asana project and task activity can be correlated alongside your other connected tools — CRM data, ad spend, revenue, docs, and tickets — inside one BI dashboard, so a question like
Just say it in a thread
No configs, no docs. Once connected, these are the kinds of messages your agents act on.
"Creates a new asana task with a name, description, assignee, and due date — and give me the highlights."
"Marks a task complete or moves it to a different section or status for me, then post a summary in the thread."
"Retrieves tasks within a specified asana project, optionally filtered by status or assignee and flag anything that needs my approval."
What teams use it for
- Ask an agent to summarize overdue tasks and blockers across all active Asana projects
- Turn a meeting transcript or Slack thread into properly assigned Asana tasks with due dates
- Let an AI assistant triage an incoming backlog and route tasks to the right project or owner
- Generate weekly status reports that blend Asana progress with revenue or ad-spend data on the BI dashboard
- Automatically update task status or add comments when related work completes in another connected tool
Agent-callable tools
create_task
Creates a new Asana task with a name, description, assignee, and due date.
update_task_status
Marks a task complete or moves it to a different section or status.
list_project_tasks
Retrieves tasks within a specified Asana project, optionally filtered by status or assignee.
add_task_comment
Adds a comment or status update to an existing Asana task.
assign_task
Assigns or reassigns a task to a specific team member.
create_project
Creates a new Asana project within a specified team or workspace.
get_project_summary
Returns a progress summary of tasks completed, overdue, and upcoming for a given project.
Your data stays yours
Credentials live in your vault. We route requests — we never store, log, or train on your data.
Works with every AI
Connect once — portable across Claude, GPT, Gemini, and every local agent you run.
Pairs well with
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Frequently asked questions
Do I need a separate Asana API key for every AI tool I use?
No — you connect Asana once through BusinessMCP.com and the same hosted MCP endpoint serves Claude, GPT, Gemini, or any other MCP-compatible agent.
Can an agent create and update tasks, or only read data?
The Asana MCP server supports both reading and writing, so agents can create tasks, update status, assign owners, and comment, not just query existing data.
Does this replace Asana's own automation rules?
It complements them — Asana rules handle deterministic workflows, while the MCP server lets AI agents make judgment-based updates and pull cross-tool context via the BI dashboard.
Keep exploring
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