MCP 服务器

cerase-media MCP

Provides multimodal understanding tools including OCR, image description, audio transcription, UI screenshot analysis, and screenshot comparison via async tools on a multimodal endpoint.

README

cerase-media MCP

First-party multimodal understanding (M-MEDIA-1 = the merge of the former cerase-ocr + cerase-transcriber): five async tools over the multimodal tool-model alias through cerase-litellm, billed per-agent. The last two (analyze_ui, compare_screenshots) are the UX/UI screenshot pair added by M-CERASE-MEDIA-UX — same multimodal endpoint, specialised prompts, no extra dependency.

Tool	Question it answers	Returns
`ocr`	what is WRITTEN in this image?	`{text, model}`
`describe_image`	what does this image SHOW?	`{description, model}`
`transcribe`	what does this audio say?	`{text, model}`
`analyze_ui`	what's in this UI screenshot? — structured audit of layout, typography, colours, interactive elements, text, visual errors, accessibility, consistency	`{analysis, model}`
`compare_screenshots`	what changed between two screenshots? — before/after visual diff (layout / text / style / new / removed / regressions)	`{diff, model}`

Image input is accepted three ways (pick one): path (a file under CERASE_TOOL_WORKSPACE_ROOT), image_url, or image_base64. compare_screenshots takes the two-image variants (path1/image1_url/ image1_base64 and path2/…).

Async by design: the tools are ~100% LLM-wait, so concurrent requests run on parallel I/O lanes inside the single runner container (no per-modality queue). ffmpeg (audio normalisation) runs as an async subprocess.

Env: LITELLM_BASE_URL, LITELLM_MASTER_KEY (scoped service key), CERASE_MULTIMODAL_ALIAS (default multimodal), CERASE_TOOL_WORKSPACE_ROOT (path-traversal guard root).