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apollo-io-mcp-server

MCP.Pizza Chef: lkm1developer

The Apollo.io MCP server is a TypeScript-based implementation that integrates the Apollo.io API with the Model Context Protocol. It enables AI assistants to access and interact with Apollo.io's extensive sales intelligence and contact data, facilitating real-time data retrieval and manipulation within AI workflows. This server supports seamless API communication, empowering developers to build AI-enhanced sales and marketing tools with structured, live context from Apollo.io.

Use This MCP server To

Retrieve detailed contact and company information from Apollo.io Integrate Apollo.io sales data into AI-driven CRM workflows Automate lead enrichment using Apollo.io API via MCP Generate real-time sales insights from Apollo.io data Enable AI assistants to query Apollo.io for prospecting Sync Apollo.io data with other business intelligence tools Trigger automated outreach based on Apollo.io contact data Aggregate Apollo.io data for market analysis and segmentation

README

Apollo.io MCP Server

TypeScript Apollo.io API MCP SDK License: MIT

A powerful Model Context Protocol (MCP) server implementation for seamless Apollo.io API integration, enabling AI assistants to interact with Apollo.io data.

Apollo.io Server MCP server

Overview

This MCP server provides a comprehensive set of tools for interacting with the Apollo.io API, allowing AI assistants to:

  • Enrich data for people and organizations
  • Search for people and organizations
  • Find job postings for specific organizations
  • Perform Apollo.io operations without leaving your AI assistant interface

Why Use This MCP Server?

  • Seamless AI Integration: Connect your AI assistants directly to Apollo.io data
  • Simplified API Operations: Perform common Apollo.io tasks through natural language commands
  • Real-time Data Access: Get up-to-date information from Apollo.io
  • Secure Authentication: Uses Apollo.io's secure API token authentication
  • Extensible Design: Easily add more Apollo.io API capabilities as needed

Installation

# Clone the repository
git clone https://github.com/lkm1developer/apollo-io-mcp-server.git
cd apollo-io-mcp-server

# Install dependencies
npm install

# Build the project
npm run build

Configuration

The server requires an Apollo.io API access token. You can obtain one by:

  1. Going to your Apollo.io Account
  2. Navigating to Settings > API
  3. Generating an API key

You can provide the token in two ways:

  1. As an environment variable:

    APOLLO_IO_API_KEY=your-api-key
    
  2. As a command-line argument:

    npm start -- --api-key=your-api-key
    

For development, create a .env file in the project root to store your environment variables:

APOLLO_IO_API_KEY=your-api-key

Usage

Starting the Server

# Start the server
npm start

# Or with a specific API key
npm start -- --api-key=your-api-key

# Run the SSE server with authentication
npx mcp-proxy-auth node dist/index.js

Implementing Authentication in SSE Server

The SSE server uses the mcp-proxy-auth package for authentication. To implement authentication:

  1. Install the package:

    npm install mcp-proxy-auth
  2. Set the AUTH_SERVER_URL environment variable to point to your API key verification endpoint:

    export AUTH_SERVER_URL=https://your-auth-server.com/verify
  3. Run the SSE server with authentication:

    npx mcp-proxy-auth node dist/index.js
  4. The SSE URL will be available at:

    localhost:8080/sse?apiKey=apikey
    

    Replace apikey with your actual API key for authentication.

The mcp-proxy-auth package acts as a proxy that:

  • Intercepts requests to your SSE server
  • Verifies API keys against your authentication server
  • Only allows authenticated requests to reach your SSE endpoint

Integrating with AI Assistants

This MCP server is designed to work with AI assistants that support the Model Context Protocol. Once running, the server exposes a set of tools that can be used by compatible AI assistants to interact with Apollo.io data.

Available Tools

The server exposes the following powerful Apollo.io integration tools:

  1. people_enrichment

    • Use the People Enrichment endpoint to enrich data for 1 person
    • Parameters:
      • first_name (string, optional): Person's first name
      • last_name (string, optional): Person's last name
      • email (string, optional): Person's email address
      • domain (string, optional): Company domain
      • organization_name (string, optional): Organization name
    • Example:
      {
        "first_name": "John",
        "last_name": "Doe",
        "email": "john.doe@example.com"
      }
  2. organization_enrichment

    • Use the Organization Enrichment endpoint to enrich data for 1 company
    • Parameters:
      • domain (string, optional): Company domain
      • name (string, optional): Company name
    • Example:
      {
        "domain": "apollo.io"
      }
  3. people_search

    • Use the People Search endpoint to find people
    • Parameters:
      • q_organization_domains_list (array, optional): List of organization domains to search within
      • person_titles (array, optional): List of job titles to search for
      • person_seniorities (array, optional): List of seniority levels to search for
    • Example:
      {
        "person_titles": ["Marketing Manager"],
        "person_seniorities": ["vp"],
        "q_organization_domains_list": ["apollo.io"]
      }
  4. organization_search

    • Use the Organization Search endpoint to find organizations
    • Parameters:
      • q_organization_domains_list (array, optional): List of organization domains to search for
      • organization_locations (array, optional): List of organization locations to search for
    • Example:
      {
        "organization_locations": ["Japan", "Ireland"]
      }
  5. organization_job_postings

    • Use the Organization Job Postings endpoint to find job postings for a specific organization
    • Parameters:
      • organization_id (string, required): Apollo.io organization ID
    • Example:
      {
        "organization_id": "5e60b6381c85b4008c83"
      }

Extending the Server

The server is designed to be easily extensible. To add new Apollo.io API capabilities:

  1. Add new methods to the ApolloClient class in src/apollo-client.ts
  2. Register new tools in the setupToolHandlers method in src/index.ts
  3. Rebuild the project with npm run build

License

This project is licensed under the MIT License - see the LICENSE file for details.

Keywords

Apollo.io, Model Context Protocol, MCP, AI Assistant, TypeScript, API Integration, Apollo.io API, People Enrichment, Organization Enrichment, People Search, Organization Search, Job Postings, AI Tools

apollo-io-mcp-server FAQ

How do I authenticate the Apollo.io MCP server?
Authentication is done via Apollo.io API keys configured in the server environment, ensuring secure access.
Can this MCP server handle rate limits imposed by Apollo.io API?
Yes, it includes mechanisms to respect Apollo.io API rate limits and retry logic.
Is the Apollo.io MCP server compatible with multiple LLM providers?
Yes, it works with OpenAI, Anthropic Claude, and Google Gemini models through the MCP protocol.
How do I extend the Apollo.io MCP server with custom API endpoints?
You can extend the TypeScript codebase by adding new handlers for Apollo.io API endpoints following MCP server conventions.
What data formats does the Apollo.io MCP server support?
It supports JSON structured data as per Apollo.io API responses, formatted for MCP consumption.
Does the server support real-time updates from Apollo.io?
It supports on-demand data fetching; real-time push updates depend on Apollo.io API capabilities.
How is security handled in the Apollo.io MCP server?
The server scopes API keys securely and limits data exposure according to MCP security principles.
Can I use this server to automate sales outreach workflows?
Yes, by integrating Apollo.io data with AI agents, you can automate personalized outreach and follow-ups.