Integration

DeepSeek integration

High-performance AI models optimized for chat, coding, and reasoning tasks. Access cost-effective language models with strong capabilities in code generation, mathematical reasoning, and multilingual conversations. Features fill-in-the-middle completion for code editing and competitive performance at lower costs.

Connect DeepSeek How integrations work

Ask it in chat

Say what should happen.
The workflow builds itself.

When this happens, do that in DeepSeek.Built from the 5 DeepSeek tools below, on the connection you add once.

Common DeepSeek use cases

Monitoring API spending
Discovering available models
Building cost-effective chatbots
Implementing code editor autocomplete
Creating responsive chat UIs with typing indicators
Implementing usage alerts
Building intelligent code assistants
Implementing dynamic model selection
Implementing function-calling agents
Building real-time conversational agents

What you can do with DeepSeek

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, 2 operations

chat_completionsChat completionsPOSTGenerate conversational responses using DeepSeek models (deepseek-v4-flash or deepseek-v4-pro).
chat_completions_streamChat completions streamPOSTStream conversational responses in real-time for interactive experiences.

Completion, 1 operation

completionsCompletionsPOSTGenerate text completions with fill-in-the-middle support for code editing.

Model, 1 operation

list_modelsList modelsGETRetrieve list of available DeepSeek models and their capabilities.

User, 1 operation

get_user_balanceGet user balanceGETCheck account balance and credit information for API usage.

Use DeepSeek from Claude Code, Cursor or Codex

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

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

DeepSeek integration FAQ

What can you do with the DeepSeek integration?

LiveContext exposes 5 operations on DeepSeek, covering chat, completion, model and user. Common uses include Monitoring API spending, Discovering available models and Building cost-effective chatbots.