> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mcp-use.com/llms.txt
> Use this file to discover all available pages before exploring further.

# LLM integration

> Connect MCPAgent to OpenAI, Anthropic, Google, Groq, or a custom LangChain chat model.

`MCPAgent` runs through LangChain chat models. You can either pass a `"provider/model"` string and let the agent create the model, or pass an existing LangChain chat model instance.

The model must support tool calling. Structured output and streaming are optional, but they are required for the corresponding `MCPAgent` features to work well.

## Use simplified mode

Simplified mode supports `openai`, `anthropic`, `google`, and `groq` provider strings. Install the matching LangChain package and set the provider API key in the environment.

| Provider string   | Package                   | API key                                            |
| ----------------- | ------------------------- | -------------------------------------------------- |
| `openai/model`    | `@langchain/openai`       | `OPENAI_API_KEY`                                   |
| `anthropic/model` | `@langchain/anthropic`    | `ANTHROPIC_API_KEY`                                |
| `google/model`    | `@langchain/google-genai` | `GOOGLE_API_KEY` or `GOOGLE_GENERATIVE_AI_API_KEY` |
| `groq/model`      | `@langchain/groq`         | `GROQ_API_KEY`                                     |

```typescript theme={null}
import { MCPAgent } from "mcp-use";

const agent = new MCPAgent({
  llm: "openai/gpt-4o",
  llmConfig: {
    temperature: 0.2,
    maxTokens: 1000,
  },
  mcpServers: {
    filesystem: {
      command: "npx",
      args: ["-y", "@modelcontextprotocol/server-filesystem", "./"],
    },
  },
});

const result = await agent.run({
  prompt: "Summarize the files in this directory.",
});

console.log(result);
await agent.close();
```

Pass `llmConfig.apiKey` when you cannot use environment variables.

```typescript theme={null}
const agent = new MCPAgent({
  llm: "anthropic/claude-sonnet-4-6",
  llmConfig: {
    apiKey: process.env.ANTHROPIC_API_KEY,
    temperature: 0,
  },
  mcpServers,
});
```

## Use explicit mode

Explicit mode accepts any LangChain-compatible chat model. Use it for custom model setup, provider-specific options, callbacks, or models not supported by simplified mode.

### OpenAI

```typescript theme={null}
import { ChatOpenAI } from "@langchain/openai";
import { MCPAgent, MCPClient } from "mcp-use";

const client = new MCPClient({ mcpServers });
const llm = new ChatOpenAI({
  model: "gpt-4o",
  temperature: 0.7,
  apiKey: process.env.OPENAI_API_KEY,
});

const agent = new MCPAgent({ llm, client });
```

### Anthropic

```typescript theme={null}
import { ChatAnthropic } from "@langchain/anthropic";
import { MCPAgent, MCPClient } from "mcp-use";

const client = new MCPClient({ mcpServers });
const llm = new ChatAnthropic({
  model: "claude-sonnet-4-6",
  temperature: 0.7,
  apiKey: process.env.ANTHROPIC_API_KEY,
});

const agent = new MCPAgent({ llm, client });
```

### Google Gemini

```typescript theme={null}
import { ChatGoogleGenerativeAI } from "@langchain/google-genai";
import { MCPAgent, MCPClient } from "mcp-use";

const client = new MCPClient({ mcpServers });
const llm = new ChatGoogleGenerativeAI({
  model: "gemini-pro",
  temperature: 0.7,
  apiKey: process.env.GOOGLE_API_KEY,
});

const agent = new MCPAgent({ llm, client });
```

### Groq

```typescript theme={null}
import { ChatGroq } from "@langchain/groq";
import { MCPAgent, MCPClient } from "mcp-use";

const client = new MCPClient({ mcpServers });
const llm = new ChatGroq({
  model: "llama-3.1-70b-versatile",
  temperature: 0.7,
  apiKey: process.env.GROQ_API_KEY,
});

const agent = new MCPAgent({ llm, client });
```

## Verify provider support

Before wiring a model into a production workflow, run one prompt that requires a tool call. If the model cannot call tools, the agent will not be able to use MCP tools even if the client connection succeeds.

For more providers, use a LangChain chat model that supports tool calling and pass it through explicit mode. See the [LangChain JavaScript chat model integrations](https://js.langchain.com/docs/integrations/chat/).

## Next steps

* [MCPAgent API Reference](/typescript/api-reference/agent/mcp-agent)