apollo-io-mcp-server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@apollo-io-mcp-serverFind senior engineers at Google"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Apollo.io MCP Server
This project provides an MCP server that exposes the Apollo.io API functionalities as tools. It allows you to interact with the Apollo.io API using the Model Context Protocol (MCP).
Overview
The project consists of the following main components:
apollo_client.py: Defines theApolloClientclass, which is used to interact with the Apollo.io API. It includes methods for people enrichment, organization enrichment, people search, organization search, and organization job postings.server.py: Defines the FastMCP server, which exposes the Apollo.io API functionalities as tools. It uses theApolloClientclass defined inapollo_client.pyto interact with the API.apollo/: Contains the data models for the Apollo.io API, such asPeopleEnrichmentQuery,OrganizationEnrichmentQuery,PeopleSearchQuery,OrganizationSearchQuery, andOrganizationJobPostingsQuery.
Related MCP server: Apollo.io MCP Server
Functionalities
The following functionalities are exposed as MCP tools:
people_enrichment: Use the People Enrichment endpoint to enrich data for 1 person.organization_enrichment: Use the Organization Enrichment endpoint to enrich data for 1 company.people_search: Use the People Search endpoint to find people.organization_search: Use the Organization Search endpoint to find organizations.organization_job_postings: Use the Organization Job Postings endpoint to find job postings for a specific organization.
Usage
To use this MCP server, you need to:
Set the
APOLLO_IO_API_KEYenvironment variable with your Apollo.io API key. Or create '.env' file in the project root withAPOLLO_IO_API_KEY.Get dependencies:
uv syncRun the
uv run mcp run server.py
Data Models
The apollo/ directory contains the data models for the Apollo.io API. These models are used to define the input and output of the MCP tools.
apollo/people.py: Defines the data models for the People Enrichment endpoint.apollo/organization.py: Defines the data models for the Organization Enrichment endpoint.apollo/people_search.py: Defines the data models for the People Search endpoint.apollo/organization_search.py: Defines the data models for the Organization Search endpoint.apollo/organization_job_postings.py: Defines the data models for the Organization Job Postings endpoint.
Testing
To test, set APOLLO_IO_API_KEY environment variable and run uv run apollo_client.py.
Usage with Claude for Desktop
Configure Claude for Desktop to use these MCP servers by adding them to your
claude_desktop_config.jsonfile:
{
"mcpServers": {
"apollo-io-mcp-server": {
"type": "stdio",
"command": "uv",
"args": [
"run",
"mcp",
"run",
"path/to/apollo-io-mcp-server/server.py"
]
}
}
}Resources
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/edwardchoh/apollo-io-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server