Supercharge your AI with Atlas. Manage everything from tickets to customers, instantly.
Works with every AI agent you already use
…and any MCP-compatible client
Connect to your AI in seconds.
Atlas MCP lets your agent manage everything in Atlas.so, connecting directly to your support data without opening a browser. You can list all open tickets, get deep details on specific customers or articles, and even create new tickets right from your chat context.
It handles customer history, team rosters, and knowledge base lookups—all through natural language commands.
What your AI can do
Create ticket
Automatically generates a brand-new support ticket record within Atlas.so.
Get account check
Verifies the connection status between your AI agent and your Atlas account credentials.
Get customer
Retrieves a full profile summary for one specific customer by name or ID.
Lists all active support tickets or generates a brand new ticket directly from conversation context.
Retrieves specific customer details, including their internal ID, name, and email address.
Searches and lists articles from your help center based on keywords or topics.
Generates a list of current team users, letting you understand who is available to handle support requests.
Pulls up the full metadata and conversation history for any given ticket ID.
Ask an AI about this
Compatible AI Apps
OAuth 2.0 CompatibleWaiting for input…
Atlas: 8 Tools for Support Automation
These tools give you granular control over the Atlas platform. You can list users, fetch customer records, create tickets, or pull article metadata using natural language prompts.
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 Atlas on VinkiusCreate Ticket
Automatically generates a brand-new support ticket record within Atlas.so.
Get Account Check
Verifies the connection status between your AI agent and your Atlas account...
Get Customer
Retrieves a full profile summary for one specific customer by name or ID.
Get Ticket
Fetches all conversation history and metadata associated with a single ticket number.
List Articles
Searches and returns a list of help center articles based on keywords you provide.
List Customers
Lists all customers in your Atlas account, allowing filtering by criteria like email or ID.
List Tickets
Retrieves a summary list of all active support tickets currently open in the system.
List Users
Shows you a roster of all current team agents and users who handle support requests.
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Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
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Start with Atlas, then connect any of our 5,000+ other servers whenever your AI needs more. One click, no limits.
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- Works with Claude, ChatGPT, Cursor, and more
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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 8 powerful capabilities that interface natively with Claude, ChatGPT, Cursor, and other compatible AI platforms. No middleware. No custom integration required.
Dealing with support means bouncing between five different web tabs.
Right now, if you need to understand a customer's issue, the process looks like this: You find their name in one tab. Then, you open another tab to see all their past tickets and what was said. After that, you switch again to look up articles about the problem they mentioned. Finally, if it’s a brand new issue, you have to manually fill out a form on yet another page.
With this MCP, you tell your agent exactly what you need—for example, 'Get me all open tickets for John Doe regarding billing.' The agent runs those calls in the background and gives you one consolidated answer. You're not juggling tabs; you're just getting the facts.
Atlas MCP: Control your entire support workflow with `create_ticket`.
The manual steps that go away are the form-filling and the status checking. You no longer have to copy a ticket ID from one screen, paste it into another system just to check its current status, or spend time searching for the right agent to assign it to.
Now, you can summarize an entire conversation, identify the core problem, and ask your agent to execute `create_ticket` immediately. The issue is logged, and the process starts without a single extra click from you.
What your AI can actually do with this
It's basically giving your AI agent full access to the Atlas support platform's backend data. Instead of having to copy IDs or navigate complex dashboards, you just ask it what you need. You can pull up a specific customer’s file, review every ticket they’ve ever opened, and check which help articles apply to their problem—all in one chat session.
This makes your agent incredibly useful for anything from onboarding new hires to auditing support processes. If you're looking for the core services of major platforms like Zendesk or Freshdesk, this MCP gives you that access, allowing your agent to act as if it’s logged into the system itself. You connect everything through Vinkius, making Atlas data available instantly alongside other tools in your catalog.
019d7554-3ce5-70ca-b726-340a55accf10 Here's how it actually works
The bottom line is: you talk naturally, the agent does the API work, and you get the answer immediately.
Your agent first uses get_account_check to verify that your Atlas.so API credentials are correctly connected.
Next, you prompt the agent with a specific request—for instance, 'Show me all open tickets for this billing issue'—and it translates that into structured data calls.
The MCP processes these tools and returns clean metadata (e.g., ticket status, customer name) directly to your chat window.
Who is this actually for?
Support Leads who are tired of jumping between ticket views and customer profile pages. Product Managers needing quick access to raw user feedback from recent tickets. Customer Success Managers who need a single source of truth on client history.
Needs to quickly look up a customer's account details and check the status of multiple past tickets without leaving their chat interface.
Must audit team bandwidth by listing all agents (list_users) or review overall support health by listing active tickets (list_tickets).
Reviews recent customer feedback, grouping common complaints found in new tickets and knowledge base articles.
What Changes When You Connect
Stop switching tabs. Instead of manually checking ticket statuses or pulling up customer profiles in separate browser windows, your agent can handle all that data retrieval—using list_tickets and get_customer—and present it back to you immediately.
Audit team capacity on demand. If you need to know who’s free before assigning a complex issue, simply call list_users. It gives you an instant overview of your support staff without navigating the internal dashboard.
Cut down response time with knowledge base access. When a customer asks about billing, instead of guessing, prompt the agent to run list_articles to pull up the exact official documentation page for that topic.
Automate initial issue logging. If you have a conversation where multiple problems are mentioned, don't waste time writing it all out; just use create_ticket and let the agent file the complaint for you.
Deep dive into history. Need to know why a customer complained last month? Use get_ticket with the specific ID. You get every piece of conversation metadata without digging through old emails.
See it in action
Customer needs immediate help.
A user asks, 'Why is my payment failing?' Your agent runs list_articles for 'Billing' and cross-references the customer using get_customer, then uses that info to create a new ticket via create_ticket if no article helps.
Manager needs an overview of today’s workload.
A manager prompts, 'What are our top 5 open issues?' The agent calls list_tickets, providing a summary list and the IDs for the most critical items needing review.
Agent needs context on an old issue.
An agent receives a chat about 'Error Code 403'. They immediately call get_ticket with the ID provided in the chat, retrieving all historical notes and previous conversations to keep the customer updated.
Identifying team bottlenecks.
A support lead asks, 'Who is available right now?' The agent calls list_users, showing who is currently logged on and free to take new cases, ensuring efficient resource allocation.
The honest tradeoffs
Trying to manually copy data.
A support lead has to open the web dashboard, find the customer's ID, then switch tabs to view their ticket history, and finally copy a relevant article link. This takes 5-10 minutes per user check.
Instead, let your agent handle it: Ask the agent to run get_customer first; this gives you the necessary details. Then, ask the agent to review all open issues for that customer using list_tickets. Finally, if documentation is needed, prompt it with list_articles.
Over-relying on basic search.
A user only searches for 'billing' in the help center and gets 50 articles. They still have to manually filter through them to find the most relevant policy document.
Use list_articles with a tighter scope, like specifying the article type or linking it directly to a customer ID retrieved via get_customer. This narrows the results down significantly.
Ignoring existing records.
When talking to a client, an agent just starts writing notes without first checking if the issue was already reported. They risk duplicating work and confusing the customer.
Before starting any new thread of conversation, always ask your agent to run list_tickets to verify if similar issues are currently open or have been recently resolved.
When It Fits, When It Doesn't
Use this MCP when your process requires synthesizing data from multiple, disparate Atlas components. Specifically, you need to cross-reference who the client is (get_customer), what problems they've had (using list_tickets and get_ticket), and what documentation exists for it all (list_articles). Don't use this if your goal is simply to draft a message; that’s pure writing. Also, don't use it if you only need to check one thing—if you just want a list of team members, running list_users directly is simpler than going through the full workflow. This MCP shines when context switching is part of your job.
Questions you might have
How does the Atlas MCP use the `list_tickets` tool? +
The agent uses list_tickets to pull a summary of all support issues. This lets your client quickly see how many tickets are open and what their general topics are, without needing to look at every single record.
Can I use the Atlas MCP to find customer info? (get_customer) +
Yes, you can. Running get_customer lets your agent pull up all key details for a specific person—like their name and account ID—which is crucial context before tackling an issue.
What if I want to file a new ticket? (create_ticket) +
You just prompt the agent with the necessary details. It uses create_ticket behind the scenes, filing the support request for you directly in Atlas without requiring manual form submissions.
Does the MCP help me find relevant articles? (list_articles) +
Absolutely. The agent runs list_articles and searches your entire knowledge base using plain language, returning a list of documentation that directly addresses the user's query.
How do I verify that my Atlas connection is set up correctly using `get_account_check`? +
The get_account_check tool immediately verifies your API token and Atlas credentials. It confirms connectivity status, letting you know right away if there are any setup issues before running deeper reports.
If I need a complete list of all my registered users, what does the `list_users` tool do? +
The list_users tool pulls a directory of every agent on your team. This helps you monitor overall support capacity and understand who is available to handle incoming requests.
I need a full list of all my clients, not just one. How do I use `list_customers`? +
list_customers retrieves the entire database roster of your clientele. This functionality lets you pull comprehensive reports or process data for mass communications.
I only have a ticket ID and need all its metadata. How can I use `get_ticket`? +
The get_ticket tool pulls the complete, detailed record for one specific ticket ID. This is ideal when you need to deep-dive into a single conversation's history or status.
How do I find my Atlas.so API Token? +
Log in to your Atlas dashboard, go to App Configuration > Data > API, and you will find your API Token there.
Can I see help center articles via this server? +
Yes, use the list_articles tool to retrieve a list of articles from your Atlas help center.
How are customer IDs handled? +
Atlas uses unique internal IDs for customers. You can discover these IDs by using the list_customers tool or searching for a specific customer by email.
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