Apollo.io Integration
STDIOHTTP-SSEMCP server implementation for seamless Apollo.io API integration, enabling AI assistants to interact with data.
MCP server implementation for seamless Apollo.io API integration, enabling AI assistants to interact with data.
A powerful Model Context Protocol (MCP) server implementation for seamless Apollo.io API integration, enabling AI assistants to interact with Apollo.io data.
This MCP server provides a comprehensive set of tools for interacting with the Apollo.io API, allowing AI assistants to:
# 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
The server requires an Apollo.io API access token. You can obtain one by:
You can provide the token in two ways:
As an environment variable:
APOLLO_IO_API_KEY=your-api-key
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
# 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
The SSE server uses the mcp-proxy-auth package for authentication. To implement authentication:
Install the package:
npm install mcp-proxy-auth
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
Run the SSE server with authentication:
npx mcp-proxy-auth node dist/index.js
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:
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.
The server exposes the following powerful Apollo.io integration tools:
people_enrichment
first_name
(string, optional): Person's first namelast_name
(string, optional): Person's last nameemail
(string, optional): Person's email addressdomain
(string, optional): Company domainorganization_name
(string, optional): Organization name{ "first_name": "John", "last_name": "Doe", "email": "[email protected]" }
organization_enrichment
domain
(string, optional): Company domainname
(string, optional): Company name{ "domain": "apollo.io" }
people_search
q_organization_domains_list
(array, optional): List of organization domains to search withinperson_titles
(array, optional): List of job titles to search forperson_seniorities
(array, optional): List of seniority levels to search for{ "person_titles": ["Marketing Manager"], "person_seniorities": ["vp"], "q_organization_domains_list": ["apollo.io"] }
organization_search
q_organization_domains_list
(array, optional): List of organization domains to search fororganization_locations
(array, optional): List of organization locations to search for{ "organization_locations": ["Japan", "Ireland"] }
organization_job_postings
organization_id
(string, required): Apollo.io organization ID{ "organization_id": "5e60b6381c85b4008c83" }
The server is designed to be easily extensible. To add new Apollo.io API capabilities:
ApolloClient
class in src/apollo-client.ts
setupToolHandlers
method in src/index.ts
npm run build
This project is licensed under the MIT License - see the LICENSE file for details.
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