kairouter-mcp
This server exposes KaiRouter's video generation API as MCP tools for AI agents to generate and manage videos.
list_video_models— list active video models with pricing and provider health (no API key required)generate_video— start async text-to-video, image-to-video, or video-to-video jobs with configurable ratio, duration, resolution, audio, and promptscheck_video_status— poll jobs by id to see queued/processing/succeeded/failed status and retrieve the video URL when donewait_for_video_job— block until a job finishes or times out, returning the final job statelist_video_jobs— view the caller's up to 50 most recent jobs
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@kairouter-mcp Generate a 5-second clip of a futuristic city at sunset using Seedance 2.0"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
kairouter-mcp
MCP server exposing KaiRouter's video generation API — BytePlus Seedance family (Seedance 2.0, 2.0 Fast, 2.0 Mini, 1.5 Pro, 1.0 Pro, ...) and any other video model active on KaiRouter — as tools any MCP-compatible agent harness (Claude Code, Codex, Antigravity, ...) can call.
This is a standalone repo — it does not contain any of KaiRouter's backend source, only a thin client for its public/user-scoped HTTP API. Not yet published to npm — run it from a local build for now (see below).
Tools
Tool | Description |
| List currently active video models on KaiRouter, with pricing and live provider health. No API key required. |
| Start an async video generation job (text-to-video or image-to-video). Returns a job id immediately — does not block until the video is ready. Spends real credits. |
| Poll a job by id. |
| Poll a job until it reaches a terminal status ( |
| List the caller's most recent jobs (up to 50), most recent first. |
generate_video is async by design — BytePlus video generation can take
tens of seconds to a few minutes. Either call generate_video once and
poll check_video_status yourself every few seconds, or call
wait_for_video_job right after to block until it's done (or times out).
Related MCP server: Gemini Omni MCP Server
Setup
git clone https://github.com/X-OR-Cloud/kairouter-mcp.git
cd kairouter-mcp
npm install
npm run buildThis produces dist/index.js. You'll need a KaiRouter API key —
create one at https://kairouter.com/dashboard/api-keys.
Claude Code
claude mcp add kairouter -e KAIROUTER_API_KEY=sk-xor-your-key-here -- node /absolute/path/to/kairouter-mcp/dist/index.jsOr add directly to .mcp.json (project) / ~/.claude.json (user):
{
"mcpServers": {
"kairouter": {
"command": "node",
"args": ["/absolute/path/to/kairouter-mcp/dist/index.js"],
"env": { "KAIROUTER_API_KEY": "sk-xor-your-key-here" }
}
}
}Codex CLI
Add to ~/.codex/config.toml:
[mcp_servers.kairouter]
command = "node"
args = ["/absolute/path/to/kairouter-mcp/dist/index.js"]
env = { KAIROUTER_API_KEY = "sk-xor-your-key-here" }Antigravity / other MCP-compatible harnesses
Most harnesses accept the same mcpServers JSON block shown above under
Claude Code — check the harness's own MCP settings for the exact config
file path/UI, since this varies and wasn't verified here for Antigravity
specifically.
Configuration
Env var | Required | Default | Notes |
| For | — | From https://kairouter.com/dashboard/api-keys. Not needed for |
| No |
| Override to point at a staging/local KaiRouter instance. |
Development
npm run dev # tsc --watch
npm start # run the built server directly over stdio (for manual testing with an MCP client)Available Tools
4 toolscheck_video_statusCheck a KaiRouter video job's statusA
Poll the status of a video generation job started with generate_video. status is one of 'queued', 'processing', 'succeeded', 'failed'. Once status is 'succeeded', video_url has the finished video. Poll every few seconds — generation typically takes tens of seconds to a few minutes depending on model and resolution.
Inputs: job_id (required).
generate_videoGenerate a video with KaiRouterA
Start an async video generation job on KaiRouter (e.g. BytePlus Seedance 2.0 / 2.0 Fast / 2.0 Mini / 1.5 Pro / 1.0 Pro — see list_video_models for the exact ids currently available). Returns immediately with a job id and status 'queued'; it does NOT wait for the video to finish. Call check_video_status with the returned id to poll until status is 'succeeded' (or 'failed'). Deducts real credits from the caller's KaiRouter account balance when the job is accepted.
Inputs: model (required), prompt (required), ratio, duration, +6 more.
list_video_jobsList recent KaiRouter video jobsA
List the caller's most recent video generation jobs (up to 50), most recent first. Useful for recovering a job id that was lost, or reviewing recent generations.
Inputs: no named parameters.
list_video_modelsList KaiRouter video modelsA
List the video generation models currently active on KaiRouter (BytePlus Seedance family and others), with id, pricing, and live provider health. Call this first to find a valid model id for generate_video — model availability changes over time, so don't assume a model id without checking here.
Inputs: no named parameters.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool has a clear, non-overlapping purpose: listing available models, listing past jobs, submitting a generation job, and polling its status. There is no ambiguity between them, and the descriptions reinforce distinct roles.
All tool names follow a consistent verb_noun pattern (list_video_models, list_video_jobs, generate_video, check_video_status). The naming is predictable and maintains the same style across the set.
With only 4 tools, the set is tightly scoped for its purpose—a video generation API router. Each tool is essential for the core workflow (discover models, generate, check status, review history) without unnecessary extras.
The toolset covers the primary lifecycle: listing models, creating a job, polling status, and retrieving past jobs. The only minor gap is the lack of cancellation or deletion options, but these are not critical for the core use case and can be worked around.
Maintenance
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