Agent.AI MCP Server

Agent.AI MCP Server

An externally deployable server designed to be hosted on Vercel that can be called from other applications, allowing integration with Agent.AI's Multi-Context Processing capabilities.

Category
Visit Server

README

Agent.AI MCP Server

This is an externally deployable version of the Agent.AI MCP Server, designed to be hosted on Vercel and called from other applications.

Deployment Instructions

Prerequisites

  • GitHub account
  • Vercel account (free tier works)
  • Git installed locally

Steps to Deploy

  1. Create a new GitHub repository

    git init
    git add .
    git commit -m "Initial commit: Agent.AI MCP Server"
    git branch -M main
    git remote add origin https://github.com/YOUR_USERNAME/agentai-mcp-server.git
    git push -u origin main
    
  2. Deploy to Vercel

    • Go to vercel.com
    • Click "New Project"
    • Import your GitHub repository
    • Vercel will automatically detect it as a Node.js project
    • Click "Deploy"
  3. Get your deployment URL

    • After deployment, Vercel will provide a URL like: https://your-project-name.vercel.app
    • This is your MCP server endpoint

Usage

Once deployed, you can call your MCP server from other applications using the Vercel URL.

Example Usage

// In your other app
const mcpServerUrl = 'https://your-project-name.vercel.app';

// Make requests to your MCP server
fetch(mcpServerUrl + '/your-endpoint')
  .then(response => response.json())
  .then(data => console.log(data));

Local Development

To run locally:

npm install
npm start

The server will start on http://localhost:3000

Configuration

  • Port: Automatically set by Vercel, or defaults to 3000 locally
  • Environment Variables: Can be set in Vercel dashboard under Project Settings > Environment Variables

Troubleshooting

  • Ensure your @agentai/mcp-server package is publicly available
  • Check Vercel deployment logs if issues occur
  • Verify your GitHub repository is public or Vercel has access

Important: Authentication Setup

1. Configure Agent.AI API Token

Your MCP server requires an Agent.AI API token to authenticate with Agent.AI services:

  1. Get your API token from Agent.AI
  2. Go to your Vercel project dashboard
  3. Click "Settings" → "Environment Variables"
  4. Add a new variable:
    • Name: API_TOKEN
    • Value: Your Agent.AI API token
  5. Redeploy the project

2. Disable Vercel Authentication

To allow external access to your MCP server, you MUST disable Vercel's built-in authentication:

  1. Go to your Vercel project dashboard
  2. Click "Settings" → "Security"
  3. Disable "Password Protection" and "Vercel Authentication"
  4. Save changes

3. Test Authentication

After setup, your endpoints will return:

  • "authentication": "configured" - Ready to use
  • "authentication": "missing" - API_TOKEN required

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured