Trello MCP Server

The Claude MCP Trello server bridges the gap between AI assistants and Trello’s rich project‑management ecosystem. It exposes a comprehensive set of Trello tools—ranging from card creation to board‑wide searches—while automatically handling the platform’s strict rate limits, type safety, and error reporting. This allows developers to focus on crafting intelligent workflows rather than wrestling with OAuth tokens or API throttling.

At its core, the server implements a token‑bucket algorithm that respects Trello’s limits of 300 requests per 10 seconds per API key and 100 requests per 10 seconds per user token. When a client hits these thresholds, the server queues subsequent calls instead of failing outright, ensuring that AI agents can request data or perform actions without interruption. Coupled with TypeScript’s static typing, every tool comes with a fully defined argument schema and exhaustive validation. If an assistant supplies an invalid list ID or omits a required field, the server returns a clear, actionable error message that can be surfaced directly to the user or logged for debugging.

Developers benefit from a ready‑made, battle‑tested integration that eliminates the boilerplate of authentication flows and API pagination. The toolset includes commands for retrieving cards by list, listing all board lists, adding or updating cards (with optional due dates and labels), archiving items, creating new lists, and even performing workspace‑wide searches. Each operation maps neatly to a single, declarative function call that an AI assistant can invoke through the MCP protocol. This simplicity translates into faster prototyping of task‑management agents, such as automated sprint planners or real‑time project dashboards.

Real‑world scenarios abound: a team could deploy an AI assistant that automatically creates backlog cards from Jira tickets, updates card statuses as developers push commits, or pulls recent activity to surface blockers in a daily stand‑up. Because the server handles authentication tokens internally, developers can embed these capabilities into chat interfaces or voice‑activated tools without exposing sensitive credentials. Moreover, the robust error handling surface ensures that users receive meaningful feedback—such as “Rate limit exceeded” or “Invalid card ID”—which can be leveraged to prompt retries or notify administrators.

In summary, the Claude MCP Trello server delivers a plug‑and‑play bridge to Trello’s API, abstracting rate limits, type safety, and error handling while exposing a rich set of project‑management tools. It empowers AI developers to integrate Trello into conversational agents, automation pipelines, or custom dashboards with minimal friction and maximum reliability.