Wing Assistant MCP for AI. Delegate work to your entire virtual team.
Works with every AI agent you already use
…and any MCP-compatible client








Connect to your AI in seconds.
The Wing Assistant MCP lets your AI agent manage and delegate work across a virtual team of digital assistants. You can list all available assistants, create new tasks with specific instructions, track task progress in real time, and update assignments programmatically.
It's the central hub for automating operational delegation workflows.
What your AI can do
Create task
Adds a new task to an assistant's queue, requiring only a title and description.
Get assistant
Fetches specific details about one particular virtual assistant account.
Get task status
Retrieves the current status and progress of a single unit of work.
Retrieves the names and details of every active virtual assistant on your account.
Pulls metadata for a single assistant, showing their assigned roles or skills.
Adds a brand-new unit of work to an assistant’s queue with a title and detailed instructions.
Displays a comprehensive list of every task currently waiting in the system.
Checks the current progress and state of any single, existing unit of work.
Updates details, instructions, or priorities on a task that has already been created.
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Wing Assistant: 6 Tools for Task Management
These tools give you full control over the lifecycle of work assigned to your virtual assistants. You can list, create, update, and track tasks programmatically.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Wing Assistant on VinkiusCreate Task
Adds a new task to an assistant's queue, requiring only a title and description.
Get Assistant
Fetches specific details about one particular virtual assistant account.
Get Task Status
Retrieves the current status and progress of a single unit of work.
List Assistants
Shows a list of all active virtual assistants connected to your account.
List Tasks
Lists every task assigned across the entire virtual assistant workspace.
Update Task
Changes instructions, details, or priorities for an existing task.
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Wing Assistant, then connect any of our 5,100+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,100+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Wing Assistant. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This connection provides 6 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
It's a mess tracking who is doing what today.
Right now, managing a virtual team means juggling five different tabs. You have the task list dashboard, the communication channel for updates, and separate sheets where you manually track deadlines. Every time something changes—a delay, an urgent pivot—you spend minutes copying IDs, changing statuses in one place, and then updating the corresponding entry everywhere else.
With this MCP, that whole process goes away. You simply tell your agent to manage the workload. It talks directly to Wing Assistant and pulls all status updates for you. The result is a single conversation where you get immediate visibility into every unit of work.
The `create_task` tool gives instant, trackable assignment.
Before this, assigning work meant writing an email, attaching a document, and hoping the recipient read it in time. It was a black box process with no automatic tracking of when or where you had delegated the item.
Now, using `create_task` is instant. The task appears immediately in the system's queue, giving you a clear record that the work started right there and that all subsequent status changes are logged.
What your AI can actually do with this
Think of this connector as your command center for running an entire remote workforce from a single chat window. Instead of logging into separate dashboards to check on projects or assign new work, you simply tell your agent what needs doing. You can list every active assistant and delegate complex tasks with clear instructions and priorities.
The system tracks the whole lifecycle—from initial assignment to final status update. This visibility means your team never loses track of who is working on what, or when a task falls behind schedule. Because this MCP integrates into Vinkius, you get full visibility via Vinkius AI Analytics; you see exactly which tasks were called and how many steps the agent took to complete them.
You can even build multi-step automations by chaining this assistant management with other services—like triggering a billing record after a task is marked complete.
019dd188-2da2-736e-8083-9f091c72b915 Here's how it actually works
The bottom line is that your agent talks directly to Wing Assistant, making the entire workflow happen without you touching any external dashboards.
First, subscribe to this MCP and enter your Wing Assistant API Access Token.
Next, tell your AI agent what you want to accomplish—for instance, 'List all assistants' or 'Create a task for X.'
The system executes the call, retrieving the data (like current status or assigned tasks), which the agent then presents back to you.
Who is this actually for?
This MCP is for Operations Managers and Founders who need reliable oversight of outsourced work. If you spend too much time manually checking statuses across multiple platforms, this connector saves your afternoon.
Manages the flow of work to virtual assistants and monitors progress in real-time without switching applications.
Needs to quickly delegate administrative or research tasks via natural conversation, eliminating manual handoffs between teams.
Scales operations by programmatically managing and assigning specialized tasks for virtual talent.
What Changes When You Connect
Stop switching apps. You can delegate complex tasks and manage assistants through natural conversation, keeping the whole process in one chat session.
Maintain a perfect audit trail. By running on Vinkius, every tool call is cryptographically signed, giving you an unalterable record of who did what and when.
Automate workflow chains. You can connect this MCP to billing or CRM tools to build automations that trigger actions across multiple platforms based on task completion.
Know your team's capacity. Use the available functions to monitor assistants’ current workload so you never overcommit a resource.
Save tokens and time. Vinkius includes native token optimization, cutting down how much compute power is needed when running complex delegation workflows.
See it in action
Tracking research output
An Ops Manager needs to know if the 'Miami real estate list' task is done. Instead of checking the dashboard, they ask their agent, which uses get_task_status and confirms completion.
Reassigning priority work
A Founder realizes a critical report needs immediate attention. They use the agent to execute update_task, raising the priority note instantly for the assistant working on it.
Onboarding new assistants
A Growth Team Lead uses list_assistants to verify which specialized virtual talent is active before assigning them a large project via create_task.
Auditing delegated tasks
An Operations Manager wants an overview of all current work. They ask the agent to run list_tasks, getting one centralized view of the entire team’s queue.
The honest tradeoffs
Over-relying on manual status checks
The user copies and pastes task IDs into multiple dashboards, checking the 'Pending' tab, then switching to a spreadsheet to see if it moved to 'In Progress'.
Instead, tell your agent to run get_task_status for that ID. The agent pulls the status directly from Wing Assistant and reports it in one go.
Creating tasks with vague instructions
The user just types 'Do research' without providing any context or required output format.
Use create_task but ensure the description includes detailed, actionable steps and a clear deadline. The more specific you are, the better the assistant performs.
Trying to change status outside the system
The user manually updates a project management tool while the MCP thinks the task is still 'In Progress'.
Always use update_task through the agent. This ensures the centralized Wing Assistant record and your audit trail are perfectly synchronized.
When It Fits, When It Doesn't
Use this MCP if you need simple, direct control over task lifecycle management—specifically creating, reading, or modifying assignments for a defined virtual team. Don't use it if your goal is complex data modeling or generating entirely new content; the tools are built for workflow orchestration, not pure generation. If your requirement involves defining multi-stage conditional logic (e.g., 'IF Task A finishes AND X happens THEN create Task B'), you may need to chain this MCP with a dedicated automation engine or use a more advanced agent framework that supports complex state machines beyond simple CRUD operations.
Questions you might have
How do I list all active virtual assistants using the `list_assistants` tool? +
You simply ask your agent to run list_assistants. The system will retrieve and display a roster of every assistant on your account, including their metadata.
Can I update task priorities using the `update_task` tool? +
Yes. You can use update_task to change instructions or priority levels for any existing assignment, keeping everyone immediately informed of the changes.
What is the difference between `list_tasks` and `get_task_status`? +
list_tasks gives you a comprehensive overview—a list of every task in the workspace. Use get_task_status when you know the specific ID or name of a single task and just need its current progress.
Does this MCP help me manage multiple virtual teams? +
Yes, by listing all assistants via list_assistants, you can monitor and delegate tasks across different specialized virtual team members through the same interface.
How do I set up authentication and tokens before running a tool like `get_assistant`? +
You must provide your Wing Assistant API Access Token in the Bearer header. This ensures your agent can connect to your specific account instance. The token acts as proof of ownership, allowing any MCP-compatible client to route commands through your secure connection.
What kind of metadata does the `get_assistant` tool provide about a virtual assistant? +
It returns detailed information including the assistant's assigned role, core skills, and operational capacity. This data lets you determine if an agent is skilled enough for a specific job before delegating it.
When I use `create_task`, what structure should I follow to make sure my delegation instructions are clear? +
A good task requires a clear title, detailed description of the work, and an explicit priority level. Providing these elements upfront minimizes back-and-forth communication and ensures the assistant starts on the right track.
If I want to see all assigned tasks across my entire workspace, how does `list_tasks` help? +
list_tasks pulls a comprehensive manifest of every unit of work in your queue. This gives you a quick view of the entire workload history and current assignments, which is useful for auditing purposes.
How do I find my Wing Assistant API Token? +
Log in to your Wing Assistant dashboard, navigate to the API section in your settings, and you will find your unique Bearer Access Token listed there.
Does this work with human-assisted tasks? +
Yes! Wing Assistant specializes in providing managed human talent. This integration allows you to send tasks to those real assistants via your AI agent.
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