Kustomer MCP. Audit customer history and data from any source.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
Kustomer. Manage customer service data by listing conversations, auditing customer records, and searching historical timelines. Connect your AI agent to Kustomer to get a 360-degree view of any customer interaction, no matter if it came through email, chat, or social media.
You can pull detailed customer profiles, search complex timelines using JSON filters, and list support queues and agents to understand your entire support structure.
What your AI agents can do
Check kustomer api status
Checks the current operational status of the Kustomer API.
Get conversation details
Retrieves specific details about a single support conversation.
Get customer profile
Gets the detailed profile for one specific customer.
Retrieves a complete profile for a specific customer, including custom attributes and history.
Lists and retrieves full message histories for conversations across multiple channels.
Performs deep, filtered searches across a customer's entire timeline using structured JSON inputs.
Retrieves a list of active support queues and the agents assigned to them.
Lists all customer IDs in Kustomer, which is necessary for large-scale auditing or reporting.
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Supported MCP Clients
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Kustomer MCP Server: 10 Tools for Support Auditing
Use these 10 tools to retrieve customer profiles, conversation details, and deep timeline history via your AI agent.
019d75c3check kustomer api status
Checks the current operational status of the Kustomer API.
019d75c3get conversation details
Retrieves specific details about a single support conversation.
019d75c3get customer profile
Gets the detailed profile for one specific customer.
019d75c3list conversation messages
Lists every message sent during a specific support conversation.
019d75c3list data klasses
Lists Kustomer's custom data classes, known as Klasses.
019d75c3list kustomer agents
Retrieves a list of all support agents (users) within Kustomer.
019d75c3list kustomer customers
Lists all customer records in Kustomer, useful for bulk auditing.
019d75c3list support conversations
Lists the most recent support conversations that occurred.
019d75c3list support queues
Lists all active support queues defined in Kustomer, such as Billing or Technical Support.
019d75c3search kustomer timeline
Performs a deep search across a customer's timeline using complex JSON filters.
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.
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Start with Kustomer, then connect any of our 4,700+ 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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What you can do with this MCP connector
You're connecting your AI agent to Kustomer. This lets your agent read and audit every piece of customer service data, pulling together profiles, conversations, and history from all channels. You can use your AI client to get a 360-degree view of any customer interaction, no matter if it came through email, chat, or social media.
Your agent can check the Kustomer API status using check_kustomer_api_status. It can grab the full profile for a specific customer with get_customer_profile, which includes custom attributes and their history. To audit support interactions, it uses get_conversation_details to get specifics on a single conversation, and list_conversation_messages to list every message sent during that support chat.
You can list all support conversations using list_support_conversations or find the most recent ones with list_support_conversations. When you need to search deep into a customer's history, your agent uses search_kustomer_timeline, which lets you run complex searches across the entire customer timeline using JSON filters. You can list all customer IDs in Kustomer using list_kustomer_customers, which is key for big audits or reporting.
To see what support structure you're dealing with, your agent lists all active support queues with list_support_queues and pulls a list of every support agent (user) with list_kustomer_agents. You can also see what custom data classes Kustomer uses by calling list_data_klasses.
How Kustomer MCP Works
- 1 First, you configure your AI client with your Kustomer Bearer API Key in the Vinkius panel.
- 2 Next, you tell your agent what you need. Example: 'Show me the full profile for customer ID 123 and list their last 10 conversations.'
- 3 Your agent uses the appropriate tools (
get_customer_profile,list_support_conversations, etc.) to gather the data and returns it to you in a single, coherent response.
The bottom line is you get a single, conversational source of truth for all your customer data, without writing any code or running complex queries.
Who Is Kustomer MCP For?
The Head of Customer Support, the Operations Engineer, and the Data Analyst. These roles need to quickly audit customer interactions across messy, siloed data. If you're tired of clicking through multiple dashboards—one for email, one for chat, and another for social—and need a single source of truth, this is for you.
Uses the agent to quickly pull a customer's full history. They need to know if the customer is a 'Platinum' member, what their lifetime value is, and what the last conversation was about before they pick up the phone.
Audits entire support queues. They use the agent to list all available support queues (list_support_queues) and check which agents are assigned to them, helping them spot staffing gaps or process bottlenecks.
Runs deep data searches. They use the agent to search the customer timeline (search_kustomer_timeline) using complex filters to find specific historical data points, like all mentions of 'API rate limit' from last quarter.
What Changes When You Connect
- Consolidate all customer data. Instead of logging into separate systems for email, chat, and social, your agent pulls everything into one view. Use
get_customer_profileto get the full 360-degree view. - Deep-dive into specific cases. Need to know exactly what was said during a support interaction? Use
list_conversation_messagesto get the full, auditable message history for any conversation. - Manage support capacity. Quickly list all active queues using
list_support_queuesand see which agents are assigned. This helps operations spot bottlenecks before they happen. - Search specific data points. Don't just browse; search.
search_kustomer_timelinelets you filter customer records using complex JSON rules, finding specific events buried in years of data. - Understand your structure. Use
list_data_klassesto see what custom data fields your team has created. This is key for building custom reporting or complex audits. - View active agents. Use
list_kustomer_agentsto get a list of every support user. This is essential if you need to verify permissions or audit who was assigned to a specific case.
Real-World Use Cases
Investigating a Recurring Bug
A tech lead needs to know why a specific customer keeps reporting the same bug. They ask their agent to 'Find every mention of the 'Login Failed' error for customer 65a4b3c2d1e0f.' The agent uses get_customer_profile and search_kustomer_timeline to pull every relevant interaction, solving the investigation in minutes.
Onboarding a New Agent
A manager needs to train a new support agent. They ask their agent to 'List all active support queues and the agents currently assigned to them.' The agent runs list_support_queues and list_kustomer_agents, providing the manager with a complete, structured overview of the current support setup.
Reviewing a High-Value Account
A CSM needs to prepare for a call with a top-tier client. They ask their agent to 'Show me the full profile for the client and all messages from the last 90 days.' The agent uses get_customer_profile and list_conversation_messages, ensuring the CSM is fully prepped with all context before the call.
Auditing Support Performance
The ops team needs a report on recent activity. They ask their agent to 'List the 10 most recent support conversations and filter them by 'Open' status.' The agent uses list_support_conversations to get the list, giving the ops team immediate visibility into pending workload.
The Tradeoffs
Copying and Pasting Data
The user manually opens the Kustomer dashboard, filters by date, copies the conversation ID, and then pastes it into a spreadsheet to check message content.
→
Instead, ask your agent to 'Get the details for conversation ID X.' The agent uses get_conversation_details and list_conversation_messages to retrieve and format all the needed information directly.
Guessing the Right Filter
A user tries to search for a customer's history but only remembers vague terms like 'billing issue' and doesn't know the specific JSON filters required for the timeline search.
→
You don't need the exact filters. Just ask the agent to 'Search the customer timeline for anything related to billing and payment in the last quarter.' The agent uses search_kustomer_timeline and structures the JSON query for you.
Checking Status Manually
The team member logs into the Kustomer UI just to see if the API is up before starting work, wasting time on status checks.
→
Start by asking the agent to 'Check the status of the Kustomer API.' This uses check_kustomer_api_status and confirms the connection is live before you run any heavy queries.
When It Fits, When It Doesn't
Use this MCP Server if your primary goal is to consolidate and audit customer data from multiple sources. You need a single, conversational interface to pull customer profiles, message histories, and support activity. It's perfect for operations teams and analysts who need a 360-degree view of a customer's entire relationship with the company.
Don't use this if you only need to read static, non-API content (like a public knowledge base article). For simple tasks, like getting a list of all customers, the list_kustomer_customers tool is straightforward. But if you need to combine that list with conversation history, you need the full power of the server.
If your workflow requires complex data manipulation (e.g., updating a customer field, triggering a payment), you might need a different type of server that handles write operations. This server is read-only, focused purely on data retrieval and auditing.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Kustomer. 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 server provides 10 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Finding a customer's full history shouldn't require jumping between 5 different tabs.
Today, finding a customer's full story is a nightmare. You open the chat tab to see the latest message. Then you have to switch to the email tab to check the original complaint. You copy the ID, switch to the social tab, and try to find the thread. You end up with five different screens, three browser tabs, and a dozen copy-pasted IDs just to get context.
With the Kustomer MCP Server, you just tell your agent, 'Give me the full history for customer 123.' The agent uses `get_customer_profile` and `list_conversation_messages` to pull the data from every source and hands it back to you in one clean report. You get the full context without the context switching.
Kustomer MCP Server: Audit Customer Data
Before this, auditing support was a manual, multi-step process. You had to run separate reports for conversations, then manually check the customer's custom attributes, and finally, cross-reference the queue assignment. It was slow, prone to human error, and rarely covered the full picture.
Now, you tell the agent, 'Search the timeline for all billing issues from Platinum members.' The agent uses `search_kustomer_timeline` and `list_support_queues` to run the complex query and provide a single, actionable list. The data you get is immediately ready for action.
Common Questions About Kustomer MCP
How do I use the list_support_queues tool in Kustomer? +
The list_support_queues tool lists all active queues (like Billing or Technical Support). You ask your agent to run it, and it provides a clean list of available queues, helping you understand your support structure.
Can I retrieve a customer's full history using get_customer_profile? +
Yes, get_customer_profile pulls more than just contact info. It fetches the complete, detailed customer record, including all custom attributes and their entire interaction history.
Is list_conversation_messages the only way to see all messages? +
No. While list_conversation_messages gets the raw messages for a specific conversation, you should start with get_conversation_details first. This gives you the overarching details, and then you can drill down to the messages.
How does search_kustomer_timeline work? +
The search_kustomer_timeline tool performs deep, filtered searches across the entire customer timeline. You just need to tell your agent what you're looking for, and it handles the complex JSON filtering.
Do I need to list_kustomer_customers before running any search? +
No. You don't need to list all customers first. You just need to provide the specific customer ID to the agent, and the tool will fetch the data directly.
What information does the list_kustomer_agents tool provide? +
It lists all active support agents and their user IDs. This is useful for auditing who handled a specific conversation or checking agent availability.
How can I use the get_conversation_details tool? +
You pass a conversation ID to get full details. This includes the conversation status, the associated customer, and the last activity timestamp.
Does the search_kustomer_timeline tool support complex filters? +
Yes, the tool accepts a JSON string for filters. You can perform deep searches across the customer's entire timeline using complex criteria.
Where do I find my Kustomer API Key? +
Log in to Kustomer, navigate to Settings > Security > API Keys, and create a new key with the necessary scopes.
Can I see chat messages in real-time? +
The list_conversation_messages tool fetches the current history. While not a streaming 'live' view, it provides the most recent state.
Does this support creating customers? +
The current version focus on data retrieval and analysis. Creation tools are planned for future updates.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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