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qwen-omni-mcp

An MCP server that gives Claude Code and other AI agents video, image, audio, and audio-video understanding via Bailian (DashScope) using the multimodal Qwen3.8-Max and Qwen3.5-Omni models.

Qwen3.8-Max reads video natively — no client-side frame extraction. Qwen3.5-Omni adds native audio understanding (and audio-track awareness for video). Pass a public media URL or a local file path; the model does the rest. The server also ships MCP instructions that teach text-only agents to reach for these tools when they need to view/read media — while telling natively multimodal agents to prefer their own vision.

Highlights

  • Native video understanding — send a video URL or local file, get grounded analysis

  • Image understanding — describe, Q&A, OCR; doubles as the "eyes" for text-only agents whose file reader can't display images

  • Audio understanding — transcribe, summarize, analyze speech/sound (mp3/wav/flac/ogg/m4a/aac)

  • Audio-video understanding — analyze a video's visuals and its sound track together

  • Thinking control — optional per-call thinking_budget on every media tool; omitted = provider default

  • Local file support — pass a local path; files are sent inline as base64 (25MB guardrail)

  • npx-launchable — one line in your MCP client config

Related MCP server: qwen-vision-mcp

Install

No global install needed. Run directly with npx:

npx -y qwen-omni-mcp

For local development:

git clone <this-repo>
cd qwen-omni-mcp
npm install            # also installs husky git hooks
cp .env.example .env   # fill in DASHSCOPE_API_KEY
npm run dev            # run from source via tsx

Configuration

All config is via environment variables (loaded from .env by dotenv):

Variable

Required

Default

Description

DASHSCOPE_API_KEY

yes

—

Bailian API key

QWEN_MODEL

no

qwen3.8-max

Model id for video/image analysis

QWEN_OMNI_MODEL

no

qwen3.5-omni-plus

Omni model id for audio/audio-video

DASHSCOPE_BASE_URL

no

https://dashscope.aliyuncs.com/compatible-mode/v1

OpenAI-compatible endpoint

QWEN_REQUEST_TIMEOUT

no

300

Per-request timeout in seconds

Get a key at https://bailian.console.aliyun.com/cn-beijing?tab=model#/api-key.

The Anthropic-compatible /apps/anthropic endpoint does not support video input, so this server uses the OpenAI-compatible endpoint.

Use with Claude Code

Add to your MCP client config:

{
  "mcpServers": {
    "qwen-omni-mcp": {
      "command": "npx",
      "args": ["-y", "qwen-omni-mcp"],
      "env": {
        "DASHSCOPE_API_KEY": "your-key"
      }
    }
  }
}

For local development without publishing:

{
  "mcpServers": {
    "qwen-omni-mcp": {
      "command": "npx",
      "args": ["tsx", "src/index.ts"],
      "env": { "DASHSCOPE_API_KEY": "your-key" }
    }
  }
}

Tools

Tool

Description

analyze_video

Analyze a video (URL or local file) with a custom prompt

analyze_image

Analyze an image (URL or local file) with a custom prompt

analyze_audio

Analyze an audio file (URL or local) with a custom prompt (Omni)

analyze_audio_video

Analyze a video's visuals + sound (URL or local) with a prompt (Omni)

check_endpoint_status

Show configured endpoint/model (key redacted)

Each media tool accepts a public http/https URL or a local file path. Local files are read and sent inline as base64, with a 25MB guardrail (verified up to a 14MB video / ~18MB body on Qwen3.7-Plus, and an 8.8MB video / ~11.7MB base64 body on Qwen3.5-Omni, both HTTP 200). Files larger than 25MB must be hosted at a public URL instead. Local input is validated by extension + magic-byte signature before encoding, so non-media files are rejected.

Each media tool also accepts an optional thinking_budget (positive integer): the maximum tokens the model may spend thinking before answering. Omit it to use the provider default (thinking on at full budget for Qwen3.8 hybrid-thinking models). Thinking tokens are billed but do not count against max_tokens, which limits the answer itself.

analyze_audio / analyze_audio_video use the omni model (QWEN_OMNI_MODEL, default qwen3.5-omni-plus) and force text-only output. Audio is sent as an input_audio block in the data:;base64,<b64> form with a format field (mp3/wav/flac/ogg/m4a/aac).

Development

npm run typecheck     # strict tsc
npm run lint          # eslint, --max-warnings 0
npm run format:check  # prettier
npm test              # unit + mocked e2e (no API cost)
npm run build         # emit dist/
LIVE=1 npm run test:live   # real API calls (costs tokens)

CI (.github/workflows/ci.yml) runs the same gates on Node 20/22. secrets-scan.yml runs gitleaks. smoke-live.yml (manual / weekly) runs one real image call.

See AGENTS.md for the full set of agent rules (never bypass hooks, never commit secrets, etc.).

License

MIT

Available Tools

5 tools
analyze_audioA

Listen to and analyze an audio file using Qwen3.5-Omni (qwen3.5-omni-plus, native audio understanding). Use this whenever you need to hear audio you cannot process natively. Pass a public URL (http/https) or a local file path; local files are sent inline as base64 (25MB guardrail, mp3/wav/flac/ogg/m4a/aac).

Inputs: audio_url (required), question, max_tokens, thinking_budget.

analyze_audio_videoA

Watch and listen to a video (visuals AND its audio track) using Qwen3.5-Omni (qwen3.5-omni-plus, native audio+video understanding). Use this when what is said or heard in the video matters. Pass a public URL (http/https) or a local file path; local files are sent inline as a base64 data URL (25MB guardrail).

Inputs: video_url (required), question, max_tokens, thinking_budget.

analyze_imageA

View, read, or analyze an image using Qwen3.8-Max (native multimodal). Use this whenever you need to see an image you cannot view natively (e.g., your file reader returns '[Unsupported Image]'). Pass a public URL (http/https) or a local file path; local files are sent inline as a base64 data URL (25MB guardrail).

Inputs: image_url (required), question, max_tokens, thinking_budget.

analyze_videoA

Watch and analyze a video using Qwen3.8-Max (native multimodal). Use this whenever you need to see a video you cannot view natively. The model reads the video natively — no client-side frame extraction. Pass a public URL (http/https) or a local file path; local files are sent inline as a base64 data URL (25MB guardrail).

Inputs: video_url (required), question, max_tokens, thinking_budget.

check_endpoint_statusA

Check the configured Bailian endpoint, model, and timeout. The API key is redacted in the output.

Inputs: no named parameters.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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    TDQS

    A4.4/5.0

    Scored across 5 tools

    Disambiguation4/5

    Most tools are clearly distinct: image, audio, and video analysis have separate tools. The only potential confusion is between analyze_video and analyze_audio_video, but the descriptions clarify that analyze_audio_video explicitly handles audio tracks as well. check_endpoint_status is unrelated and unambiguous.

    Naming Consistency4/5

    The primary tools follow a consistent analyze_<media_type> pattern (analyze_video, analyze_image, analyze_audio, analyze_audio_video). The utility tool check_endpoint_status deviates from this pattern but still follows the verb_noun structure. Overall, the naming is predictable and easy to navigate.

    Tool Count5/5

    With 5 tools, the server is well-scoped for its purpose of multimodal analysis. It covers all major media types (image, audio, video, audio+video) and includes a utility check. The count is neither too thin nor bloated.

    Completeness5/5

    The tool set provides complete coverage for the stated domain of media analysis: images, audio, video, and video with audio. The endpoint status tool adds necessary operational visibility. There are no obvious missing operations for the server's purpose.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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