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:
- 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
- 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
# Clone the repository
git clone https://github.com/rollingstone87/apollo-mcpo.git
cd apollo-mcpo
# Build Image from the repo
docker built -t apollo-mcp .{
"mcpServers": {
"apollo-mcpo-server": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"--network", "mcp-network",
"-e", "APOLLO_IO_API_KEY=your_api_key",
"apollo-mcp-image"
]
}
}
}# Start the server
docker run -d --name mcpo-docker-tools -p 8001:8000 --network mcp-network -v /path/to/config-docker-apollo.json:/app/config-docker-apollo.json -v /var/run/docker.sock:/var/run/docker.sock -e APOLLO_IO_API_KEY="your_api_key" mcpo-docker:latest mcpo --config /app/config-docker-apollo.json
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
- Use the People Enrichment endpoint to enrich data for 1 person
- Parameters:
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
- Example:
{ "first_name": "John", "last_name": "Doe", "email": "john.doe@example.com" }
-
organization_enrichment
- Use the Organization Enrichment endpoint to enrich data for 1 company
- Parameters:
domain(string, optional): Company domainname(string, optional): Company name
- Example:
{ "domain": "apollo.io" }
-
people_search
- Use the People Search endpoint to find people
- Parameters:
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
- Example:
{ "person_titles": ["Marketing Manager"], "person_seniorities": ["vp"], "q_organization_domains_list": ["apollo.io"] }
-
organization_search
- Use the Organization Search endpoint to find organizations
- Parameters:
q_organization_domains_list(array, optional): List of organization domains to search fororganization_locations(array, optional): List of organization locations to search for
- Example:
{ "organization_locations": ["Japan", "Ireland"] }
-
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" }
The server is designed to be easily extensible. To add new Apollo.io API capabilities:
- Add new methods to the
ApolloClientclass insrc/apollo-client.ts - Register new tools in the
setupToolHandlersmethod insrc/index.ts - Rebuild the project with
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