For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://modelgates.ai/docs/_mcp/server.
Client SDKs
The Client SDKs give you a thin, type-safe layer over the ModelGates REST API. It handles authentication, request validation, and response typing so you can call any of 300+ models with a single function call — no boilerplate, no provider-specific quirks.
Install instructions
| Language | Package | Install |
|---|---|---|
| TypeScript | @modelgates/sdk | npm install @modelgates/sdk |
| Python | modelgates | pip install modelgates |
| Go | go-sdk | go get github.com/ModelGatesTeam/go-sdk |
All three SDKs are auto-generated from the ModelGates OpenAPI spec, so new models, parameters, and endpoints appear immediately after each API release.
When to use the Client SDKs
Choose the Client SDKs when you need direct, efficient access to model inference and want to manage your own application logic:
- Single-turn completions — send a prompt, get a response
- Streaming responses — real-time token-by-token output
- Embeddings, video, and rerank — generate vector representations, create videos, and rerank results
- API key and credit management — programmatic control over your account
- Custom orchestration — you handle conversation loops, tool dispatch, and state yourself
The Client SDKs are intentionally lean. It mirrors the ModelGates API surface 1:1 with full type safety, so there is no abstraction to fight when you need fine-grained control.
If you want higher-level primitives for building agents — multi-turn loops, tool definitions, stop conditions, and conversation state management — see the Agent SDK instead.
Quick example
import ModelGates from '@modelgates/sdk'; const client = new ModelGates({ apiKey: process.env.MODELGATES_API_KEY,}); const response = await client.chat.send({ model: 'openai/gpt-5.2', messages: [ { role: 'user', content: 'Explain quantum computing in one sentence.' }, ],}); console.log(response.choices[0].message.content);from modelgates import ModelGatesimport os with ModelGates(api_key=os.getenv("MODELGATES_API_KEY")) as client: response = client.chat.send( model="openai/gpt-5.2", messages=[ {"role": "user", "content": "Explain quantum computing in one sentence."} ], ) print(response.choices[0].message.content)Client SDKs vs Agent SDK
| Client SDKs | Agent SDK | |
|---|---|---|
| Focus | Lean API client — mirrors the REST API with full type safety | Agentic primitives — multi-turn loops, tools, stop conditions |
| Use when | You want direct model calls and manage orchestration yourself | You want built-in agent loops, tool execution, and state management |
| Conversation state | You manage it | Managed for you via callModel |
| Tool execution | You dispatch tool calls | Automatic with the tool() helper |
| Languages | TypeScript, Python, Go | TypeScript |
Next steps
- TypeScript SDK reference
- Python SDK reference
- Go SDK reference
- Agent SDK overview — for building agents with multi-turn loops and tools