Chattermill MCP Server for Cursor 11 tools — connect in under 2 minutes
Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.
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{
"mcpServers": {
"chattermill": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
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About Chattermill MCP Server
Connect your Chattermill account to any AI agent and take full control of your customer experience (CX) intelligence through natural conversation. Unify feedback from Zendesk, App Store, Typeform, and dozens of other sources into one AI-powered view.
Cursor's Agent mode turns Chattermill into an in-editor superpower. Ask Cursor to generate code using live data from Chattermill and it fetches, processes, and writes. all in a single agentic loop. 11 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
What you can do
- Project Management — List and inspect all feedback projects configured in your account
- Feedback Intelligence — Browse, filter, and paginate customer responses with full date and source filtering
- Theme Analysis — Explore AI-generated themes and categories to pinpoint recurring customer issues
- Metric Insights — Retrieve calculated NPS, CSAT, net sentiment, and volume metrics on demand
- Source Auditing — List all data sources and data types feeding your feedback pipeline
- Segmentation — Access custom segments for advanced cohort analysis
- Data Ingestion — Submit new feedback entries for analysis directly from your agent
The Chattermill MCP Server exposes 11 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Chattermill to Cursor via MCP
Follow these steps to integrate the Chattermill MCP Server with Cursor.
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
Save the file
Cursor will automatically detect the new MCP server
Start using Chattermill
Open Agent mode in chat and ask: "Using Chattermill, help me...". 11 tools available
Why Use Cursor with the Chattermill MCP Server
Cursor AI Code Editor provides unique advantages when paired with Chattermill through the Model Context Protocol.
Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
Cursor's Composer feature can generate entire files using real-time data fetched through MCP. no copy-pasting from external dashboards
MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
Chattermill + Cursor Use Cases
Practical scenarios where Cursor combined with the Chattermill MCP Server delivers measurable value.
Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP
Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically
Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates
Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data
Chattermill MCP Tools for Cursor (11)
These 11 tools become available when you connect Chattermill to Cursor via MCP:
get_chattermill_metric
Valid metric_type values: nps, average_score, net_sentiment, volume. Supports optional date range filtering with UNIX timestamps. Retrieve a calculated metric (NPS, CSAT, sentiment, volume) for a project
get_chattermill_project
Use list_chattermill_projects first if the project ID is unknown. Get details of a specific Chattermill project by its ID
get_response_details
Returns the comment, score, metadata, and applied themes. Get detailed information for a single feedback response
list_chattermill_projects
Use this first to obtain the project key needed by all other Chattermill tools. The project key is typically a lowercase version of the company name. List all available feedback projects in the Chattermill account
list_custom_segments
Returns user-defined segments used for advanced filtering and cohort analysis. List custom segments defined for a project
list_data_types
Returns data classification types used to categorize responses. Use this to discover type keys for filtering. List all feedback data types for a project (e.g. NPS, review, survey)
list_feedback_responses
Supports pagination via page/per_page and date filtering via date_from/date_to in YYYYMMDD_HHMMSS format. Default: page 1, 20 results per page, max 100. List paginated feedback responses for a specific project
list_feedback_sources
Returns configured data ingestion sources. Use this to discover available source keys for filtering responses. List all feedback data sources for a project (e.g. Zendesk, App Store, Typeform)
list_feedback_themes
Returns themes automatically generated by Chattermill ML to classify recurring customer topics. List AI-generated feedback themes detected in a project
list_theme_categories
Categories are parent groupings for themes, useful for high-level trend analysis. List categories that group feedback themes together
submit_feedback_response
Requires the project_key plus comment text. Optionally supply score, data_source, and data_type keys from their respective list endpoints. Submit a new feedback response to a Chattermill project
Example Prompts for Chattermill in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with Chattermill immediately.
"List all my Chattermill projects and then show me the latest feedback responses from the first one."
"What is our current NPS score for the 'acme' project?"
"Show me the AI-detected themes and their categories for my mobile app project."
Troubleshooting Chattermill MCP Server with Cursor
Common issues when connecting Chattermill to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
Chattermill + Cursor FAQ
Common questions about integrating Chattermill MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.Can Cursor use MCP tools in inline edits?
How do I verify MCP tools are loaded?
Connect Chattermill with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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GitHub Copilot in VS Code with Agent mode and MCP support.
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Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Chattermill to Cursor
Get your token, paste the configuration, and start using 11 tools in under 2 minutes. No API key management needed.