Fillout.io MCP Server

The Danielma Tic Fillout Mcp Server bridges the gap between AI assistants and the powerful form‑management capabilities of Fillout.io. By exposing a clean, authenticated MCP interface, developers can let Claude or other AI agents create, update, and analyze forms without writing custom integration code. The server handles token validation, request throttling, and error mapping so that AI workflows remain robust and secure.

At its core, the server offers three main functional pillars: Form Management, Response Handling, and Analytics. Form Management lets agents list, retrieve, create, update, or delete forms on demand—ideal for dynamic survey generation or onboarding processes that adapt to user context. Response Handling allows the AI to submit answers, fetch past submissions, filter by date or status, and export data for downstream processing. Analytics features expose completion rates, average response times, and trend metrics, giving agents the ability to report on engagement or quality in real time.

Key features include a set of well‑documented tools such as , , and . Each tool accepts simple, declarative parameters—like form names or question arrays—and returns JSON objects that can be consumed directly by the AI. The server also enforces strict API key rules, distinguishing between live and test keys, providing clear error messages for common authentication pitfalls, and offering rate‑limit handling to keep the integration compliant with Fillout.io’s usage policies.

In real‑world scenarios, this MCP server shines in environments where rapid iteration of data collection is required: e.g., a customer support bot that creates custom feedback forms on the fly, or a product research assistant that gathers user responses and immediately visualizes trends. By integrating with existing AI workflows, developers can skip boilerplate code, reduce latency, and focus on higher‑level logic—such as interpreting analytics or generating follow‑up actions based on form data.

Unique advantages of the Danielma Tic implementation include its comprehensive error troubleshooting guide, which anticipates common token and rate‑limit issues, and its seamless Docker configuration for Claude Desktop users. The server’s modular design ensures that adding new tools—like advanced filtering or custom calculation logic—can be done without disrupting existing AI agents. For developers who already rely on MCP for tool integration, this Fillout.io server provides a ready‑to‑use, secure bridge to robust form management and analytics.