Miro MCP Server

The Miro MCP Server bridges the gap between AI assistants and collaborative whiteboards by exposing Miro’s rich API as a set of programmable tools. Developers can now let an AI agent create, modify, and organize board content—sticky notes, shapes, connectors, documents, and more—directly through the Model Control Protocol. This eliminates the need for manual API calls or custom wrappers, allowing AI workflows to treat Miro as a first‑class data source and action platform.

Problem Solved

Modern AI assistants thrive on structured, actionable APIs. Miro, however, offers a sprawling REST interface that is cumbersome to integrate manually, especially when developers want to automate board management or embed real‑time collaboration into conversational agents. The Miro MCP Server automatically translates the official OpenAPI specification into a set of standardized tools, providing a consistent interface that any MCP‑compliant client can consume. This removes boilerplate code, reduces integration friction, and guarantees that the AI always interacts with the most up‑to‑date Miro capabilities.

What It Does

Once running, the server listens for MCP requests on a single endpoint () and translates each call into an authenticated Miro API request. The tool set covers every major board element:

• Board operations: fetch or update the entire board.
• Item CRUD: create, read, update, and delete sticky notes, text boxes, shapes, cards, images, documents, embeds, app cards, and connectors.
• Positioning: adjust an item’s coordinates or parent relationship.
• Filtering and pagination for bulk queries.

Because the tools mirror Miro’s native endpoints, AI agents can compose complex workflows—such as automatically clustering notes, generating visual summaries, or synchronizing external data sources—without needing to understand the underlying HTTP details.

Key Features & Capabilities

• Automatic Tool Generation: The server parses the OpenAPI spec on startup, ensuring that every public endpoint becomes a ready‑to‑use MCP tool.
• Full Board Coverage: All core Miro item types are supported, enabling end‑to‑end board manipulation.
• Position & Hierarchy Control: Move items or reparent them, facilitating dynamic layout adjustments driven by AI logic.
• Scalable Item Retrieval: Pagination and filtering let agents pull large batches of items efficiently, making it practical for boards with hundreds or thousands of objects.
• Extensibility: Adding new Miro endpoints is as simple as updating the OpenAPI spec; no code changes are required.

Use Cases & Real‑World Scenarios

• Automated Ideation Sessions: An AI facilitator can generate sticky notes from user prompts, cluster them into themes, and reorganize the board in real time.
• Data‑Driven Visualizations: Pull data from external APIs, create charts or cards on the board, and update them as data changes—all orchestrated by an assistant.
• Project Management Integration: Sync task cards with a project tracker, automatically updating status or positioning based on milestones.
• Collaborative Design Review: Let an AI agent annotate a shared board, add connectors between design elements, and provide instant feedback on layout or consistency.
• Educational Tools: Teachers can use the server to populate boards with lesson materials, quizzes, and interactive elements that respond to student input.

Integration with AI Workflows

Because the server follows MCP standards, any compliant client—Claude, GPT‑4o, or custom agents—can invoke Miro tools with a single JSON payload. The AI can:

1. Query the board to gather context.
2. Decide on actions (e.g., “create a sticky note with this idea”).
3. Execute the action through the MCP tool.
4. Iterate, using responses to refine subsequent calls.

This tight loop enables truly autonomous assistants that can manage visual collaboration spaces, turning a static board into an interactive, AI‑powered workspace.

The Miro MCP Server is a lightweight yet powerful gateway that transforms collaborative whiteboards into programmable assets, empowering developers to weave Miro’s visual language directly into AI‑driven applications.