Integration

Qwen integration

Alibaba's Qwen series of large language models for multilingual AI applications. Access powerful models for Chinese and English conversations, code generation, and reasoning tasks. Features competitive performance and extensive capability across diverse use cases.

Connect Qwen How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Qwen.Built from the 6 Qwen tools below, on the connection you add once.

Common Qwen use cases

Creating marketing visuals
Polling image generation status
Building image-based Q&A systems
Building bilingual semantic search
Creating responsive chat interfaces
Building Chinese-English bilingual chatbots
Generating custom illustrations
Monitoring batch processing jobs
Building real-time dialogue systems
Creating search-enhanced assistants

What you can do with Qwen

Each of these is one operation on one endpoint, available both as a workflow step and as a tool an AI agent can call on its own. Nothing bundles several operations into one action, so what a run did stays readable afterwards.

Most endpoints run on the free plan. A few, mainly the ones that publish on your behalf, need a paid plan.

Chat, 3 operations

chat_completionsChat completionsPOSTGenerate conversational responses using Alibaba's Qwen large language models.
chat_completions_streamChat completions streamPOSTStream Qwen chat responses incrementally for real-time applications.
multimodal_conversationMultimodal conversationPOSTEngage in multimodal conversations combining text and images with Qwen-VL.

Embedding, 1 operation

text_embeddingText embeddingPOSTConvert text into semantic embeddings optimized for Chinese and English.

Image, 1 operation

image_generationImage generationPOSTCreate images from text prompts using Alibaba's Wanx image generation model.

Task, 1 operation

get_task_resultGet task resultGETRetrieve results from asynchronous long-running tasks.

Use Qwen from Claude Code, Cursor or Codex

Connect Qwen in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Qwen operations become tools the client can call, next to every other integration you connected.

Claude Code

claude mcp add --transport http livecontext https://livecontext.ai/mcp --header "X-API-Key: YOUR_API_KEY"

Codex (~/.codex/config.toml)

[mcp_servers.livecontext]
url = "https://livecontext.ai/mcp"

[mcp_servers.livecontext.http_headers]
"X-API-Key" = "YOUR_API_KEY"

Cursor, Claude Desktop and other JSON configs

{
  "mcpServers": {
    "livecontext": {
      "type": "http",
      "url": "https://livecontext.ai/mcp",
      "headers": {
        "X-API-Key": "YOUR_API_KEY"
      }
    }
  }
}

Set up the MCP server step by step

How to connect Qwen

Create your workspace
Sign up free. Nothing to install.
Connect Qwen once
Add your Qwen connection in Settings. Every tool from this integration reuses it, and secrets are encrypted at rest and visible only to you.
Describe the job in chat
The workflow builds itself in front of you and picks the endpoints it needs. Drag the steps yourself on the canvas whenever you would rather be explicit.

Qwen integration FAQ

What can you do with the Qwen integration?

LiveContext exposes 6 operations on Qwen, covering chat, embedding, image and task. Common uses include Creating marketing visuals, Polling image generation status and Building image-based Q&A systems.