Integration

Moonshot AI integration

Chinese AI assistant platform with strong capabilities in Chinese language understanding. Access conversational AI for customer service, content generation, and knowledge applications. Features long context support and competitive pricing for Chinese market applications.

Connect Moonshot AI How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in Moonshot AI.Built from the 14 Moonshot AI tools below, on the connection you add once.

Common Moonshot AI use cases

Monitoring API credit usage
Monitoring batch job status
Polling for batch completion
Stopping erroneous batch jobs
Cleaning up outdated documents
Checking file processing status
Large-scale document processing
Previewing extracted file content
Managing uploaded document inventory
Uploading documents for Q&A sessions

What you can do with Moonshot AI

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.

File, 5 operations

files_contentFiles contentGETRetrieve extracted text content from an uploaded file.
files_deleteFiles deleteDELETERemove an uploaded file from storage permanently.
files_getFiles getGETRetrieve detailed information about a specific uploaded file.
files_listFiles listGETRetrieve list of uploaded files available for use as context.
files_uploadFiles uploadPOSTUpload documents for extraction and use as conversation context.

Batch, 4 operations

batch_cancelBatch cancelPOSTCancel an in-progress batch job.
batch_createBatch createPOSTCreate a batch job to process multiple chat completion requests asynchronously.
batch_getBatch getGETRetrieve status and details for a specific batch job.
batch_listBatch listGETList all batch processing tasks in the account.

Chat, 2 operations

chat_completionsChat completionsPOSTGenerate conversational responses using Kimi models with extended context windows.
chat_completions_streamChat completions streamPOSTStream chat responses in real-time with long-context support.

Account, 1 operation

get_balanceGet balanceGETRetrieve account balance including available, voucher, and cash balances.

Model, 1 operation

list_modelsList modelsGETRetrieve available Kimi models with different context window sizes.

Token, 1 operation

estimate_tokensEstimate tokensPOSTCalculate token count for messages to manage context window usage.

Use Moonshot AI from Claude Code, Cursor or Codex

Connect Moonshot AI in LiveContext, create an API key in Settings, then add the LiveContext MCP server to your client. Its Moonshot AI 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 Moonshot AI

Create your workspace
Sign up free. Nothing to install.
Connect Moonshot AI once
Add your Moonshot AI 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.

Moonshot AI integration FAQ

What can you do with the Moonshot AI integration?

LiveContext exposes 14 operations on Moonshot AI, covering file, batch, chat and account. Common uses include Monitoring API credit usage, Monitoring batch job status and Polling for batch completion.