Trello MCP Server

The MCP Server Trello solves a common pain point for developers building AI‑powered assistants: accessing and manipulating Trello data without wrestling with the platform’s REST API, rate limits, or type safety. By exposing a rich set of tools that mirror Trello’s core concepts—boards, lists, cards, checklists, attachments, and activity streams—the server lets AI agents query, update, and orchestrate project workflows directly from natural language prompts. This abstraction frees developers from boilerplate code while ensuring that every interaction respects Trello’s usage policies and delivers consistent, well‑typed responses.

At its core, the server offers full board integration. An AI assistant can list all cards in a given board, retrieve nested details such as comments and member assignments, or move cards between lists with a single tool call. The ability to extract complete card data—including checklists, attachments, labels, and history—enables agents to generate comprehensive reports or summaries that a human would otherwise assemble manually. Moreover, the server supports file attachments from arbitrary URLs, allowing agents to enrich cards with PDFs, images, or videos without requiring the user to download and re‑upload files.

Key capabilities are designed for robustness: built‑in rate limiting automatically throttles requests to meet Trello’s 300 requests/10s per API key and 100 requests/10s per token limits, preventing service interruptions. The implementation is type‑safe and written in TypeScript, providing compile‑time guarantees that tool inputs match Trello’s expectations. Coupled with input validation and graceful error handling, developers can trust that the server will return informative messages rather than cryptic HTTP errors. The dynamic board selection feature lets agents switch contexts between multiple workspaces on the fly, making it ideal for organizations that manage several projects simultaneously.

Real‑world use cases abound. A project manager could ask an AI assistant to “move all cards with the Urgent label from Backlog to Sprint 1,” and the server would execute that action with a single tool call. A knowledge worker might request a markdown export of all cards in a board, receiving a human‑readable summary that can be shared with stakeholders. Teams integrating Trello into continuous‑delivery pipelines could trigger card updates in response to CI/CD events, enabling automated status tracking. Because the server exposes its tools through MCP, any AI client that understands the protocol—Claude, Gemini, or custom agents—can seamlessly incorporate Trello operations into broader conversational workflows.

In summary, the MCP Server Trello delivers a high‑performance, developer‑friendly bridge between AI assistants and Trello’s rich project management ecosystem. Its emphasis on type safety, rate‑limit compliance, and comprehensive card manipulation makes it a standout choice for anyone looking to embed Trello interactions into intelligent applications without the overhead of custom API handling.