About seedance-prompts-mcp
seedance-prompts-mcp gives MCP clients a library of 150 AI video prompts that have each been rendered into a video. Users can search and inspect examples, audit drafts, and compose prompts, making it useful for developing video descriptions from actual outputs.
Key features
- 01Search 150 video prompts
- 02View English and Japanese text with clips
- 03Filter by category and reference-image use
- 04Audit drafts against seven elements
- 05Compose prompts and identify unset fields
Use cases
- 01Find examples for product ads and other videos
- 02Inspect the video produced by a prompt
- 03Check drafts for missing camera, lighting, or sound details
- 04Build structured prompts with timeline beats
MCP support
The MCP server provides tools for search, prompt retrieval, category listing, draft auditing, and prompt composition. Its prompt data is bundled, so runtime use needs no API key or network access.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
5Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| limit | number | No | Max results, default 10, max 50. |
| query | string | No | Free text, English or Japanese (e.g. "neon street", "product commercial", "one take morphing"). |
| category | enum | No | Restrict to one category.person | anime | food | product | animal | scenery | vehicle | scifi | physics | cinematic |
| needs_reference_image | boolean | No | true = only image-to-video prompts that expect a reference image. |
Details
From the project READMESeedance Prompts MCP
150 AI video prompts that were each actually rendered into a video. Search them, read the full text in English and Japanese, watch the clip the prompt produced, audit your own draft against what the rendered prompts specify, or compose a new one — all from your MCP client.
Most "prompt library" packages ship prompts nobody ran, so you find out what a prompt does only after you spend a generation on it. Here the clip came first: every entry links to the video that this exact text produced, and the audit tool measures your draft against all 150 of them rather than against someone's opinion of good prompting.
Add it to your client with the two lines below, then ask it to find you a prompt.
Install
Node 18+. No dependencies, no API key, no network access at runtime — the prompt set is bundled.
{
"mcpServers": {
"seedance-prompts": {
"command": "npx",
"args": ["-y", "seedance-prompts-mcp"]
}
}
}
Claude Desktop: claude_desktop_config.json. Cursor: .cursor/mcp.json. Any other stdio MCP
client takes the same two lines.
Tools
| Tool | What it does |
|---|---|
search_prompts | Free-text search over 150 prompts (English or Japanese), filter by category or by whether the prompt expects a reference image. |
get_prompt | Full English + Japanese prompt text, the example video URL, and where to run it. |
list_categories | The ten categories and how many prompts each holds. |
check_prompt | Audits a draft against the seven elements measured across all 150 rendered prompts — style, scene, subject, camera, lighting, sound, timeline. Names what is missing, why it matters, and hands you a real prompt to copy from. |
build_prompt | Composes those seven elements plus timeline beats into the bracket format the rendered prompts use, and tells you which fields you left to the model. |
Why the audit is worth running
The seven elements are not a style guide someone invented — they are counted over the bundled set at load time. Across the 150 rendered prompts, camera work is specified in half of them and audio in far fewer: those two are where drafts most often leave the result to chance. Seedance 2 generates audio together with the video, so an unspecified soundtrack is a decision you handed over rather than a field you skipped.
check_prompt("A woman turns around in a neon alley at night")
→ 2/7 · missing: camera work, lighting, sound, timeline …
each with the reason it matters and a rendered prompt to copy the phrasing from
Example
search_prompts({ query: "product commercial", limit: 3 })
get_prompt({ slug: "perfume-product-advertisement-generation-prompt-for-seedance-2-0" })
→ prompt_en, prompt_ja, example_video (mp4), source
Where the prompts come from
They are the public prompt library of Emaki, a Japanese
AI video site running Seedance 2 and Seedance 2.5. Each entry there has the prompt, the settings
and the resulting clip. 32 of the 150 are image-to-video prompts that show how to address
multiple reference images (@Image1, @Image2) — the part that is hardest to guess.
Pick a prompt and run it in the browser: text to video · image to video · Seedance 2.5 (up to 30 seconds with audio in one pass).
License
MIT. The prompt texts are published by Emaki for reuse; the example videos stay on Emaki's CDN.
Python build
The same server for uvx users lives on PyPI as
seedance-prompts-mcp — same five tools, same
bundled prompts, standard library only. Source is in python/; the prompt data is copied from
src/prompts.json at publish time so the two builds cannot drift apart.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.