by peakmojo
mcp-hubspot is a Model Context Protocol (MCP) server that connects AI assistants directly to HubSpot CRM data. It enables AI models to interact with and manage HubSpot contacts, companies, and engagement data, enhancing CRM workflows and data retrieval.
mcp-hubspot is a Model Context Protocol (MCP) server that enables AI assistants, such as Claude, to interact directly with HubSpot CRM data. It acts as a bridge between AI models and your HubSpot account, providing access to contacts, companies, and engagement data. The server incorporates built-in vector storage (using FAISS) and caching mechanisms to overcome HubSpot API limitations and improve response times.
mcp-hubspot can be easily deployed via Docker. You can install it using Smithery CLI (recommended) with npx -y @smithery/cli@latest install mcp-hubspot --client claude or pull the Docker image directly using docker run -e HUBSPOT_ACCESS_TOKEN=your_token buryhuang/mcp-hubspot:latest. For manual configuration in Claude desktop, a JSON snippet is provided for mcpServers configuration. Building the Docker image locally is also an option.
hubspot_create_contact, hubspot_create_company, hubspot_get_company_activity, hubspot_get_active_companies, hubspot_get_active_contacts, hubspot_get_recent_conversations, and hubspot_search_data.crm.objects.contacts (read/write), crm.objects.companies (read/write), and sales-email-read scopes for your HubSpot access token.hubspot_create_contact and hubspot_create_company tools include duplicate prevention mechanisms.-v flag in the Docker run command.A Model Context Protocol (MCP) server that enables AI assistants to interact with HubSpot CRM data. This server bridges AI models with your HubSpot account, providing direct access to contacts, companies, and engagement data. Built-in vector storage and caching mechanisms help overcome HubSpot API limitations while improving response times.
Our implementation prioritizes the most frequently used, high-value HubSpot operations with robust error handling and API stability. Each component is optimized for AI-friendly interactions, ensuring reliable performance even during complex, multi-step CRM workflows.
Create HubSpot contacts and companies from this LinkedIn profile:
[Paste LinkedIn profile text]
What's happening lately with my pipeline?
The server offers tools for HubSpot management and data retrieval:
| Tool | Purpose |
|---|---|
hubspot_create_contact |
Create contacts with duplicate prevention |
hubspot_create_company |
Create companies with duplicate prevention |
hubspot_get_company_activity |
Retrieve activity for specific companies |
hubspot_get_active_companies |
Retrieve most recently active companies |
hubspot_get_active_contacts |
Retrieve most recently active contacts |
hubspot_get_recent_conversations |
Retrieve recent conversation threads with messages |
hubspot_search_data |
Semantic search across previously retrieved HubSpot data |
You'll need a HubSpot access token with these scopes:
# Install via Smithery (recommended)
npx -y @smithery/cli@latest install mcp-hubspot --client claude
# Or pull Docker image directly
docker run -e HUBSPOT_ACCESS_TOKEN=your_token buryhuang/mcp-hubspot:latest
For manual configuration in Claude desktop:
{
"mcpServers": {
"hubspot": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "HUBSPOT_ACCESS_TOKEN=your_token",
"-v", "/path/to/storage:/storage", # Optional persistent storage
"buryhuang/mcp-hubspot:latest"
]
}
}
}
To build the Docker image locally:
git clone https://github.com/buryhuang/mcp-hubspot.git
cd mcp-hubspot
docker build -t mcp-hubspot .
For multi-platform builds:
docker buildx create --use
docker buildx build --platform linux/amd64,linux/arm64 -t buryhuang/mcp-hubspot:latest --push .
pip install -e .
MIT License
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