TinyPNG MCP Server

The TinyPNG MCP Server bridges the gap between AI assistants and image‑compression services by exposing TinyPNG’s powerful optimization API as a first‑class tool in the Model Context Protocol ecosystem. Developers who rely on Claude or other MCP‑enabled assistants can now compress images—whether stored locally or hosted remotely—directly from within conversational workflows, eliminating the need for separate CLI commands or manual API calls. This integration is especially valuable in creative pipelines, web development, and content‑management systems where image size directly impacts load times, bandwidth usage, and user experience.

At its core, the server offers two intuitive tools: compress_local_image and compress_remote_image. The former accepts an absolute file path, optional output location, and desired format, while the latter requires only a URL. Both tools validate inputs against a shared schema that guarantees correct paths and supported MIME types, ensuring reliable operation across platforms. The underlying TinyPNG API key is injected via environment variables, keeping credentials secure and allowing the same server instance to serve multiple projects with different keys if needed.

Key capabilities include:

• Seamless integration into AI workflows—Claude can invoke compression as part of a larger task such as preparing assets for a website or optimizing images before uploading to cloud storage.
• Flexible output control—developers can choose the destination path and format, making it easy to replace originals or generate multiple variants.
• Support for both local and remote images—the server automatically handles HTTP downloads, error handling, and retries, freeing assistants from low‑level networking concerns.
• Security by design—the server runs behind the MCP protocol, so sensitive API keys never leave the host environment and are only transmitted over encrypted channels.

Real‑world scenarios that benefit from this MCP server include:

• A designer working with Claude to generate mockups can immediately compress the resulting images before sharing them on a staging site.
• A web developer automating build scripts can ask Claude to optimize all assets in a directory, then deploy the compressed bundle with minimal manual intervention.
• A content manager can schedule nightly compression jobs for newly uploaded media, ensuring that a website’s image load times stay optimal without additional scripting.

Because the TinyPNG MCP Server is packaged as a lightweight Node or Bun executable, it can be deployed on local machines, CI pipelines, or cloud functions with minimal overhead. Its straightforward schema definitions and environment‑based configuration make it a plug‑and‑play component for any AI‑driven image‑processing workflow, giving developers the power to reduce file sizes on demand while maintaining full control over output quality and format.