Miro MCP Server

The mcp-miro server bridges Claude and the MIRO whiteboard platform, turning a cloud‑based visual workspace into an interactive AI‑powered tool. By exposing MIRO’s REST API through the Model Context Protocol, developers can embed real‑time board manipulation directly into AI assistant workflows. This eliminates the need to switch between a browser and an AI interface, enabling seamless creation, editing, and retrieval of visual content from within Claude’s conversational context.

At its core, the server offers a set of high‑level resources and tools that mirror MIRO’s native capabilities. Users can fetch the entire board state, read individual frames or elements, and perform bulk operations such as creating dozens of sticky notes or shapes in a single request. The ability to generate stickies from image input—by having Claude analyze a photo and translate it into MIRO objects—is especially powerful for rapid prototyping or visual brainstorming. Developers can also instruct the AI on board coordinates, layer ordering, and formatting through dedicated prompts, giving fine‑grained control over the visual output.

Key features include:

• Board Content Retrieval – Pull a full snapshot of a board’s elements, enabling the AI to analyze or transform existing visuals.
• Element Creation – Create sticky notes, shapes, and other objects with precise positioning, color, and text.
• Bulk Operations – Execute mass insertions or updates, reducing round‑trips and improving performance for large diagrams.
• Prompt Guidance – Custom prompts that teach the AI how to interpret board coordinates, frames, and styling conventions.
• OAuth Integration – Securely authenticate via an environment variable or command‑line token, keeping credentials out of the codebase.

Real‑world scenarios benefit from this integration: design teams can ask Claude to draft a mind map, generate wireframes, or annotate existing diagrams on the fly; educators can have AI produce interactive lesson boards; project managers might request automatic task board updates based on conversation context. The server’s design aligns with typical AI‑first workflows: a user speaks to Claude, the assistant issues an MCP command like “create sticky at (x, y)”, and the server translates that into a MIRO API call—all without leaving the chat interface.

What sets mcp‑miro apart is its focus on visual intelligence. By leveraging Claude’s image analysis and natural language understanding, the server can transform photos of hand‑drawn notes into structured MIRO objects with remarkable fidelity. This capability turns a simple snapshot into an editable, searchable board element, dramatically speeding up collaborative ideation. Combined with the flexibility of MCP’s tool and prompt system, developers gain a powerful, extensible bridge between conversational AI and visual collaboration platforms.