MCP Server

Installation

npm install @monitoro/herd

Basic Setup

Here’s how to create an MCP server that exposes web application functionality:

import { HerdMcpServer } from '@monitoro/herd';

const server = new HerdMcpServer({
    info: {
        name: "gmail-assistant",
        version: "1.0.0",
        description: "Gmail automation tools for LLMs"
    },
    transport: {
        type: "sse",
        port: 3000
    },
    herd: {
        token: "your-herd-token"  // Get from herd.garden
    }
});

// Start the server
await server.start();

Creating Web App Tools

Tools encapsulate web application functionality for LLMs. Here are some examples:

// Gmail: Compose new email
server.tool({
    name: "composeEmail",
    description: "Compose and send a new email",
    schema: {
        to: z.string().email(),
        subject: z.string(),
        body: z.string()
    }
}, async ({ to, subject, body }, devices) => {
    const device = devices[0];
    const page = await device.newPage();
    
    // Navigate to Gmail compose
    await page.goto('https://mail.google.com/mail/u/0/#compose');
    
    // Fill out the email form
    await page.type('input[aria-label="To"]', to);
    await page.type('input[aria-label="Subject"]', subject);
    await page.type('div[aria-label="Message Body"]', body);
    
    // Send the email
    await page.click('div[aria-label="Send"]');
    
    return { success: true };
});

// Twitter: Post a tweet
server.tool({
    name: "postTweet",
    description: "Post a new tweet",
    schema: {
        content: z.string().max(280)
    }
}, async ({ content }, devices) => {
    const device = devices[0];
    const page = await device.newPage();
    
    await page.goto('https://twitter.com/compose/tweet');
    await page.type('div[aria-label="Tweet text"]', content);
    await page.click('div[data-testid="tweetButton"]');
    
    return { success: true };
});

Creating Web App Resources

Resources provide structured data from web applications:

// Gmail: Unread emails
server.resource({
    name: "unreadEmails",
    uriOrTemplate: "gmail/unread",
}, async (devices) => {
    const device = devices[0];
    const page = await device.newPage();
    
    await page.goto('https://mail.google.com/mail/u/0/#inbox');
    
    // Extract unread email information
    const emails = await page.evaluate(() => {
        return Array.from(document.querySelectorAll('tr.unread'))
            .map(row => ({
                sender: row.querySelector('.sender').textContent,
                subject: row.querySelector('.subject').textContent,
                date: row.querySelector('.date').textContent
            }));
    });
    
    return { emails };
});

// LinkedIn: Profile Information
server.resource({
    name: "linkedinProfile",
    uriOrTemplate: "linkedin/profile/{username}",
}, async ({ username }, devices) => {
    const device = devices[0];
    const page = await device.newPage();
    
    await page.goto(`https://www.linkedin.com/in/${username}`);
    
    // Extract profile information
    return await page.extract({
        name: 'h1',
        headline: '.headline',
        about: '.about-section p',
        experience: '.experience-section li'
    });
});

Complete Example: Twitter Assistant

Here’s a complete example showing how to create an MCP server that provides Twitter automation capabilities to LLMs:

import { HerdMcpServer } from '@monitoro/herd';
import { z } from 'zod';

const server = new HerdMcpServer({
    info: {
        name: "twitter-assistant",
        version: "1.0.0",
        description: "Twitter automation for LLMs"
    },
    transport: {
        type: "sse",
        port: 3000
    },
    herd: {
        token: process.env.HERD_TOKEN
    }
});

// Post a tweet
server.tool({
    name: "postTweet",
    description: "Post a new tweet",
    schema: {
        content: z.string().max(280)
    }
}, async ({ content }, devices) => {
    const device = devices[0];
    const page = await device.newPage();
    await page.goto('https://twitter.com/compose/tweet');
    await page.type('div[aria-label="Tweet text"]', content);
    await page.click('div[data-testid="tweetButton"]');
    return { success: true };
});

// Get timeline
server.resource({
    name: "timeline",
    uriOrTemplate: "twitter/timeline",
}, async (devices) => {
    const device = devices[0];
    const page = await device.newPage();
    await page.goto('https://twitter.com/home');
    
    return await page.extract({
        tweets: {
            _$r: 'article[data-testid="tweet"]',
            author: '[data-testid="User-Name"]',
            content: '[data-testid="tweetText"]',
            stats: {
                likes: '[data-testid="like"]',
                retweets: '[data-testid="retweet"]'
            }
        }
    });
});

// Like a tweet
server.tool({
    name: "likeTweet",
    description: "Like a tweet by its URL",
    schema: {
        tweetUrl: z.string().url()
    }
}, async ({ tweetUrl }, devices) => {
    const device = devices[0];
    const page = await device.newPage();
    await page.goto(tweetUrl);
    await page.click('div[data-testid="like"]');
    return { success: true };
});

// Start the server
server.start().then(() => {
    console.log('Twitter Assistant ready!');
}).catch(console.error);

This setup allows LLMs to:

1. Post tweets
2. Read the timeline
3. Like tweets
4. All through your local browser, maintaining your security and privacy