Gyazo MCP Server

The Gyazo MCP Server bridges the gap between AI assistants and visual content by exposing Gyazo’s image repository through the Model Context Protocol. Developers can now treat screenshots, screen recordings, and other captured media as first‑class resources within AI workflows. This eliminates the need for manual file transfers or custom APIs, allowing assistants to reference images by simple URIs and retrieve rich metadata in a single request.

At its core, the server offers three pillars of functionality: resources, tools, and metadata enrichment. Resources represent individual Gyazo images, each accompanied by original binary data, descriptive tags, and optional OCR text. The toolset includes search (), retrieval (, ), and upload () commands. These tools translate natural language queries into API calls, returning structured results that AI assistants can parse and embed directly in responses. For example, a user might ask for “the most recent screenshot of my app’s login page,” and the assistant will fetch, decode, and display the image inline.

Real‑world scenarios that benefit from this server are abundant. In product design reviews, a team can prompt an assistant to pull the latest UI mockup from Gyazo and annotate it on the fly. QA engineers can request screenshots that match a specific error message, automatically retrieving relevant captures for debugging sessions. Content creators can generate image‑rich prompts for creative writing or marketing copy by querying images based on title, app source, or date ranges. The upload tool enables developers to programmatically seed new images, ensuring that the assistant’s knowledge base stays current without manual intervention.

Integration into AI workflows is straightforward: once the server is registered in a client’s MCP configuration, tools become available as callable actions. The assistant can chain operations—searching for images, fetching the best match, and inserting it into a generated report—all while maintaining context across turns. Because each image resource carries metadata, downstream processes such as sentiment analysis or accessibility checks can be performed without additional data fetches.

What sets Gyazo MCP Server apart is its seamless fusion of visual data with structured metadata and OCR support, all delivered through a lightweight TypeScript implementation. Developers gain instant access to an external image service without wrestling with authentication or rate limits, thanks to the server’s built‑in token handling. The result is a powerful, developer‑friendly bridge that transforms static screenshots into dynamic, AI‑driven assets.