Integrate Chattermill with Claude, Cursor, Chatbots & AI Agents MCP Server
GDPR Free for SubscribersCompatible with every major AI agent and IDE
GeminiGet chattermill metric on Chattermill
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 on Chattermill
Use list_chattermill_projects first if the project ID is unknown. Get details of a specific Chattermill project by its ID
Get response details on Chattermill
Returns the comment, score, metadata, and applied themes. Get detailed information for a single feedback response
List chattermill projects on Chattermill
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 on Chattermill
Returns user-defined segments used for advanced filtering and cohort analysis. List custom segments defined for a project
List data types on Chattermill
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 on Chattermill
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 on Chattermill
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 on Chattermill
Returns themes automatically generated by Chattermill ML to classify recurring customer topics. List AI-generated feedback themes detected in a project
List theme categories on Chattermill
Categories are parent groupings for themes, useful for high-level trend analysis. List categories that group feedback themes together
Submit feedback response on Chattermill
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
Security & Code Integrity Audit
Every tool in the Chattermill MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.
How Vinkius protects your data
Is there a risk of the AI "going crazy" and deleting important company data?
No. With Vinkius, the AI operates on "rails". It can only make the exact moves you authorized in the tool's settings. It cannot invent routes, access other networks in your company, or decide to delete random files. If the action isn't in the approved catalog, the attempt is blocked instantly.
Where do I find my Chattermill API Key?
Log in to your Chattermill account and navigate to Settings > API. You can generate and copy your personal API Key from that section. The key is used as a Bearer token on every API request.
What happens if the underlying API rate limits my agent?
Our edge infrastructure automatically handles backoffs, queueing, and throttling. If an AI agent sends too many erratic requests, Vinkius manages the rate limits gracefully, ensuring your backend doesn't crash.
What if the AI ends up reading customer data or confidential information?
We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.
Chattermill Capabilities for AI Assistants
Add the Chattermill tool to your AI Agents. The toolkit allows Claude and ChatGPT to securely fetch and update targeted data.
Next-Gen sentiment analysis Operations
The Chattermill MCP translates LLM intent into specific sentiment analysis actions. Agents like Cursor use this to interface securely with your customer support infrastructure.
Autonomous nps Strategies
The Chattermill toolkit enables AI agents to execute nps commands. It handles protocol translation for customer support integrations natively.
Chattermill. Runs on everything.
From IDE to framework. Every connection governed by Vinkius.
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
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.
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