# Build Your Twitter Agent

## Creating a Twitter Agent with Alith

In this tutorial, you will learn how to create a Node.js application that integrates X/Twitter with Alith’s Model Context Protocol (MCP) feature. This allows you to use LLM models and agents to fetch tweets from a specific user, post a new tweet, like a tweet, quote a tweet, etc.

*Note: Although we used Node.js in this tutorial, you can still use Alith Rust SDK and Python SDK to complete this Twitter agent.*

<a href="https://alith.vercel.app/docs" class="button primary">Get Started</a>

### Prerequisites

Before starting, ensure you have the following:

* **OpenAI API Key:** Sign up at OpenAI and get your API key or use your favorite LLM models.
* **Node.js 18+ environment and pnpm.**
* **A X/Twitter account.**

### Install Required Libraries

Initialize the project and install the necessary Node.js libraries using pnpm:

```bash
mkdir alith-twitter-example && cd alith-twitter-example && pnpm init
pnpm i alith
pnpm i --save-dev @types/json-schema
```

### Set Up Environment Variables

#### LLM API Key

Store your API keys and tokens as environment variables for security:

```bash
export OPENAI_API_KEY="your-openai-api-key"
```

#### Cookie Authentication

```bash
export AUTH_METHOD=cookies
export TWITTER_COOKIES=["auth_token=your_auth_token; Domain=.twitter.com", "ct0=your_ct0_value; Domain=.twitter.com"]
```

**To obtain cookies:**

1. Log in to Twitter in your browser.
2. Open Developer Tools (F12).
3. Go to the Application tab > Cookies.
4. Copy the values of auth\_token and ct0 cookies.

#### Username/Password Authentication

```bash
export AUTH_METHOD=credentials
export TWITTER_USERNAME=your_username
export TWITTER_PASSWORD=your_password
export TWITTER_EMAIL=your_email@example.com  # Optional
export TWITTER_2FA_SECRET=your_2fa_secret    # Optional, required if 2FA is enabled
```

#### API Authentication

```bash
export AUTH_METHOD=api
export TWITTER_API_KEY=your_api_key
export TWITTER_API_SECRET_KEY=your_api_secret_key
export TWITTER_ACCESS_TOKEN=your_access_token
export TWITTER_ACCESS_TOKEN_SECRET=your_access_token_secret
```

### Write the Typescript Code

Create a Typescript script (e.g., index.ts) and add the following code:

*Note: We need to install `tsc` firstly.*

```typescript
import { Agent } from "alith";
 
const agent = new Agent({
  name: "A twitter agent",
  model: "gpt-4",
  preamble: "You are a automatic twitter agent.",
  mcpConfigPath: "mcp_twitter.json",
});

console.log(await agent.prompt("Search Twitter for tweets about AI"));
console.log(await agent.prompt('Post a tweet saying "Hello from Alith Twitter Agent!"'));
console.log(await agent.prompt("Get the latest tweets from @OpenAI"));
console.log(await agent.prompt("Chat with Grok about quantum computing"));
```

### Write the MCP Config

Create a JSON file named `mcp_twitter.json` and add the following code:

```json
{
  "mcpServers": {
    "agent-twitter-client-mcp": {
      "command": "npx",
      "args": ["-y", "agent-twitter-client-mcp"],
      "env": {
        "AUTH_METHOD": "cookies",
        "TWITTER_COOKIES": "[\"auth_token=YOUR_AUTH_TOKEN; Domain=.twitter.com\", \"ct0=YOUR_CT0_VALUE; Domain=.twitter.com\", \"twid=u%3DYOUR_USER_ID; Domain=.twitter.com\"]"
      }
    }
  }
}
```

### Run the Application

Run your Typescript script to start and test the application:

```bash
npx tsc && node index.js
```


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.lazai.network/agent-onchain-kit-alith/build-your-twitter-agent.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.