zvex MCP server

AI video dubbing as an MCP tool: hand it a video URL or a local file, get back a fully dubbed video in Russian, English or Spanish — keeping the original speakers' voices through per-speaker voice cloning.

Powered by zvex (声桥).

The server is a thin stdio client over zvex's HTTP API, so it runs anywhere Python does — no GPU, no local models.

Install

uvx zvex                # run it without installing anything
# or
uv tool install zvex    # install the `zvex` command
# or
pip install zvex

(Working from a source checkout instead? Use uv tool install ./mcp/zvex.)

Get an API key

1. Sign in at https://tts.xalhar.top
2. Open Account → API keys and create one
3. Copy the zvex-… value — it is shown only once

Jobs are billed from the same credit balance as the web app, at a flat 10 credits per minute of video. A failed job is refunded in full. Top-up supports WeChat Pay, Alipay and PayPal.

Configure your MCP client

Claude Desktop (claude_desktop_config.json) or Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "zvex": {
      "command": "uvx",
      "args": ["zvex"],
      "env": {
        "ZVEX_API_KEY": "zvex-your-key-here"
      }
    }
  }
}

Tools

Typical flow — public URL:

submit_dubbing_job(video_url="https://example.com/episode-01.mp4", target_language="ru")
  → {"job_id": 42, "credits_cost": 240, "duration_sec": 1441.0, …}
wait_for_job(42)
  → {"status": "completed", "final_video_url": "…", "subtitle_url": "…"}

Typical flow — local file (no public URL needed):

upload_video("/home/me/clip.mov")
  → {"file_id": "a1b2c3d4e5f60718", "duration_sec": 92.4, …}
submit_dubbing_job(file_id="a1b2c3d4e5f60718", target_language="ru")
  → {"job_id": 43, …}

Notes

• submit_dubbing_job takes exactly one of video_url or file_id.
• video_url must be a publicly reachable http(s) link, up to 500 MB.
• upload_video sends the file to the server (up to 500 MB); the uploaded copy persists, so one upload can back several submissions.
• target_language depends on the deployment (ru, en, es on the hosted service).
• tier is fast, standard or professional — it selects which features are available, not the price.
• One job per account runs at a time; a second submission returns HTTP 409.
• Output links are signed, time-limited URLs (valid ~24 h) — they download without signing in. Re-poll the job to get a fresh link once one expires.

No expert mode over MCP — use the web app for that

The MCP tools are the fully automatic path: you hand over a video URL and get back a finished dub, with no review step in between. That is deliberate — an LLM client has no way to listen to a waveform or judge whether a line landed.

Expert mode is not exposed as an MCP tool. For the full expert mode, go to tts.xalhar.top and open an order's Review page (/expert/{run_id}).

What you get there, and why it is worth the trip:

In short: MCP is the "just give me the video" path; the web app's expert mode is where you fix the 5% that a machine cannot judge. Run the automatic pass over MCP first, then open the same order in the web app whenever the result needs a human ear.

Alipay AI Pay agents (zero sign-up)

If your agent is wired into Alipay AI Pay (the A2M 402 protocol — OpenClaw-style clients), you can skip sign-up and top-up entirely and pay per call:

Flow: call without credentials → 402 + Payment-Needed signed bill → pay via Alipay AI Pay → retry with Payment-Proof → resource delivered. Dubbing is asynchronous; poll /a2m/v1/dubbing/status/{out_trade_no} for the finished video and subtitles.

Both services are live on the Alipay AI Pay service bazaar (search "声桥" or "zvex"). Protocol details: https://tts.xalhar.top/docs/mcp. Regular MCP clients without 402 support should use the API-key path above.

Development

uv venv --python 3.11 .venv-test
uv pip install --python .venv-test/bin/python -e .
ZVEX_API_KEY=zvex-… .venv-test/bin/python -m zvex.server