Generates and edits images and videos through OpenAI and Google Veo, with MCP-aware media downloads and file outputs.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
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π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Media Gen MCP.
fetch-imagesCallable MCP tool function
test-imagesCallable MCP tool function
resource_linkCallable MCP tool function
ResourceLinkCallable MCP tool function
imageCallable MCP tool function
ImageContentCallable MCP tool function
strato-space/media-gen-mcp MCP server provides MCP tools for creating and editing images, generating videos, managing asynchronous video jobs, and retrieving media assets. OpenAI image operations support the gpt-image-1.5 and gpt-image-1 models. The image workflow covers text-to-image generation and edits such as inpainting, outpainting, and compositing, with support for one to 16 input images.
For video, the server supports OpenAI Videos with Sora models, including job creation, remixing, listing, retrieval, deletion, and content downloads. Google GenAI support uses Veo video generation operations, including starting an operation, polling its status, and downloading completed MP4 output. The server also includes tools for fetching images, videos, and documents from HTTP(S) URLs or local filesystem paths.
The server is implemented in strict TypeScript and returns MCP CallToolResult objects. Depending on the tool and response options, media can be returned as inline image or resource content, as resource_link entries pointing to files on disk, or through structured output. Image responses can be placed in content, structuredContent, or at the top level for testing and client compatibility checks.
Downloaded and generated assets are written to disk with generated filenames. Image and document names include a generated identifier, while video names can use the OpenAI video ID. For images, the server can automatically choose file-based output when an inline response would exceed a safe size threshold. Optional Sharp-based processing can compress images by reducing quality and dimensions.
The repository provides a local installation flow based on cloning the project, installing its npm dependencies, and building the TypeScript source:
The standard build performs strict type checking, including library checks. An npm run esbuild mode is also documented for faster bundling without type checking. The supplied material does not specify the credential variable names, client configuration JSON, or the command used to launch the built server, so those details should be checked in the repository before deployment.
The strato-space/media-gen-mcp MCP server includes these documented capability groups:
test-images tool.isError: true and a text error item.The server depends on the OpenAI and Google GenAI APIs for the corresponding generation features, so model availability and provider-side behavior apply. Video generation may be asynchronous; the OpenAI create tool and Google generation tool can optionally wait, while separate retrieval tools handle existing jobs or operations.
Inline media responses may not be suitable for every MCP client or payload size. The server therefore offers file-backed resource_link and embedded resource forms, but clients must support the selected MCP result shape to consume them correctly. Image compression is user-controlled and disabled by default. The provided material also indicates that DALLΒ·E support is planned rather than describing it as an available generation path.
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