Polaria MCP for AI Agents. Automate support tasks and manage contacts instantly.
Polaria MCP unifies your customer support workflow by connecting Polaria directly to your agent. It lets your AI automatically manage live chats, pull specific contact details, and search through your entire knowledge base of FAQs without you ever leaving your central workspace.
Give Claude and any AI agent real-world access
The agent can list all contacts or retrieve specific details about a user to get context for support.
It automatically reads and adds replies to current chat conversations, keeping the dialogue moving forward.
The agent can update a support ticket's status (e.g., from Open to Resolved) directly through conversation management.
It pulls relevant FAQ articles, helping the AI respond accurately without needing human intervention for basic queries.
The agent can list existing widgets or conversations to give you an overview of your support environment.
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What AI agents can do with Polaria: 8 Tools for Customer Operations
Use these eight tools to manage the full lifecycle of customer interactions, from creating a new contact record to adding a final message to a resolved chat.
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 Polaria MCPCreate Contact
Adds a brand new person's contact record into Polaria.
Add Chat Message
Posts a message reply or update to an existing customer conversation thread.
Get Contact
Pulls all the detailed information for one specific contact person.
Get Conversation
Retrieves the full history and details of a single chat conversation.
List Contacts
Generates a list of all contacts stored in Polaria for review.
List Conversations
Shows an overview and summary of multiple ongoing chat conversations.
List Faqs
Fetches a list of available knowledge articles or Frequently Asked Questions.
List Widgets
Lists all the functional widgets that can be used within your Polaria workspace.
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 each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Polaria, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Polaria. 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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The constant tab-switching cycle of modern support work Solved with Vinkius AI Gateway
Today, solving one customer issue means opening at least three different windows: the main chat window to talk to them; the contact management system to verify who they are and what account they have; and finally, the internal wiki or FAQ section to find the correct policy answer. You end up copy-pasting details between systems until your fingers hurt.
With this MCP, you simply tell your agent what needs doing. It pulls the customer data, finds the right article via list_faqs, and writes the reply—all in one go. Your AI client manages the handoffs so you don't have to.
Polaria MCP: Manage contacts, conversations & FAQs
The need to manually update a support ticket status is gone. Instead of logging into Polaria and finding the specific conversation thread just to click 'Resolved,' you prompt your agent to handle it after you've finished the chat.
It’s not about automation for automation’s sake; it’s about keeping context alive. You get a unified, intelligent layer that knows how to read your chats, check user records, and update statuses without human intervention.
What your AI can actually do with this
This MCP connects your AI client directly into the core functions of Polaria. Your agent instantly handles everything from reading a new chat message to finding the right article in your help center. It retrieves relevant support articles, allowing it to respond accurately and quickly. You can also manage customer records, listing all contacts or pulling specific user details needed for follow-up.
The system keeps track of conversations, so it knows exactly where things stand—whether a ticket is open, pending, or resolved. Connecting Polaria via Vinkius lets you use these tools across any MCP-compatible client, giving your team one single point of control over every customer interaction.
019dd13e-fb1c-730d-8996-16fc389aba89 Here's how it actually works
The bottom line is that you'll get a unified view of customer service actions right inside your natural language agent.
Log into your Polaria dashboard and navigate to Settings > Marketplace. You'll create a new app there to generate your Secret Key.
Connect the MCP via Vinkius, providing the necessary credentials to link your AI client to Polaria’s services.
Your agent can now execute commands like listing contacts or adding chat messages, bringing all support data into conversation.
Who is this actually for?
This MCP is for the customer success manager who spends half their day copying data between dashboards. It’s for support agents tired of switching tabs just to update a ticket status or look up an FAQ article. If your job involves high-volume communication and constant context switching, this is built for you.
Responding to live chats by first using list_contacts to check user details, then adding a reply message to move the conversation forward.
Getting an overview of recent activity by listing conversations and tracking ticket status changes across multiple users.
Finding quick answers for recurring user questions by calling list_faqs to pull the exact policy or guide needed.
What Changes When You Connect
Update ticket status directly. Instead of manually changing a status in the dashboard, you can instruct your agent to update it (Open, Pending, or Resolved) right after resolving the chat.
Never lose context again. Use get_contact and list_contacts to pull up necessary user details before responding, ensuring every communication is personalized and informed.
Instant knowledge retrieval. You can call list_faqs so your agent pulls authoritative answers from your internal knowledge base, speeding up resolution time for common questions.
Keep track of everything in one place. The ability to list_conversations gives you a quick snapshot of all active chats without having to navigate multiple tabs.
Build new records on the fly. Use create_contact when you handle an inquiry from someone not yet in your system, ensuring zero gaps in your customer data.
See it in action
Handling a Complex Billing Inquiry
A user asks about a billing discrepancy. Your agent uses list_contacts to confirm the account holder's details, then calls list_faqs to find the specific invoicing policy, and finally uses add_chat_message to provide a clear, accurate answer in the chat.
Onboarding New Enterprise Clients
The agent receives an inquiry for a new partnership. It calls get_contact to check if the user is already tracked, and then uses create_contact to log them into Polaria's system immediately.
End of Service Cycle Cleanup
A long-running chat thread needs closure. The agent reviews all conversations via list_conversations, determines the issue is fixed, and uses get_conversation to confirm details before updating the status.
Troubleshooting a Widget Issue
A user reports a broken feature widget. Your agent calls list_widgets to see what functions are available, identifies the faulty one, and routes the issue internally by adding a message to track it.
The honest tradeoffs
What to watch out for, and the recommended way to handle each one.
Manual Data Syncing
Opening Polaria, manually copying customer names into a CRM sheet, then opening that sheet to find the correct chat ID.
You simply ask your agent to list_contacts and get_contact. It handles the data retrieval and organization automatically before you write a single line of code.
Forgetting Context
A support agent having to switch between three different tabs (tickets, users, FAQs) just to answer one question.
By using list_faqs and get_contact together, your agent pulls all the context—user history plus official policy—into one reply.
Guessing Statuses
Assuming a ticket is resolved when the customer hasn't acknowledged it.
Use get_conversation to review the full chat thread, then use add_chat_message to send a follow-up and finally update the status correctly.
When It Fits, When It Doesn't
You should use this MCP if your support team relies on constant context switching across contacts, conversations, and knowledge articles. If you need an AI agent that can read data (list_contacts, list_faqs) AND perform actions (add_chat_message, update ticket status), this is the right fit. Don't use it if your only goal is simple chat transcription; those are general messaging tools. Also, don't rely on this just for creating internal user groups; that requires a separate identity management tool. Use it because it connects Polaria's operational data directly into your agentic workflow.
Questions you might have
How do I list contacts using the Polaria MCP? +
You ask your agent to use list_contacts. The tool returns a comprehensive list of all people in your system, letting you see who needs attention or data cleanup.
Can I update my support ticket status with Polaria MCP? +
Yes. You can instruct the agent to manage the conversation and automatically update the ticket's status (Open, Pending, Resolved) when the issue is closed out in chat.
Does Polaria MCP help me find FAQs? +
The list_faqs tool lets your agent access your internal knowledge base. This means it can provide accurate answers drawn from your official documentation.
What if I need to add a new customer record? Is that part of Polaria MCP? +
Absolutely. Use create_contact when you handle an inquiry from someone who isn't yet in your system. It logs them instantly so you don’t lose their data.
Can I get details on a specific chat conversation with Polaria MCP? +
Yes, the get_conversation tool retrieves the entire history of any given chat thread, giving your agent all the context needed to reply accurately.