HubSpot MCP Server

A Model Context Protocol (MCP) server that enables AI assistants to interact with HubSpot CRM data, providing built-in vector storage and caching mechanisms help overcome HubSpot API limitations while improving response times.

HubSpot MCP Server

Docker Hub License: MIT

Overview

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.

Why MCP-HubSpot?

  • Direct CRM Access: Connect Claude and other AI assistants to your HubSpot data without intermediary steps
  • Context Retention: Vector storage with FAISS enables semantic search across previous interactions
  • Zero Configuration: Simple Docker deployment with minimal setup

Example Prompts

Create HubSpot contacts and companies from this LinkedIn profile:
[Paste LinkedIn profile text]
What's happening lately with my pipeline?

Available Tools

The server offers tools for HubSpot management and data retrieval:

ToolPurpose
hubspot_create_contactCreate contacts with duplicate prevention
hubspot_create_companyCreate companies with duplicate prevention
hubspot_get_company_activityRetrieve activity for specific companies
hubspot_get_active_companiesRetrieve most recently active companies
hubspot_get_active_contactsRetrieve most recently active contacts
hubspot_get_recent_conversationsRetrieve recent conversation threads with messages
hubspot_search_dataSemantic search across previously retrieved HubSpot data

Performance Features

  • Vector Storage: Utilizes FAISS for efficient semantic search and retrieval
  • Thread-Level Indexing: Stores each conversation thread individually for precise retrieval
  • Embedding Caching: Uses SentenceTransformer with automatic caching
  • Persistent Storage: Data persists between sessions in configurable storage directory
  • Multi-platform Support: Optimized Docker images for various architectures

Setup

Prerequisites

You'll need a HubSpot access token with these scopes:

  • crm.objects.contacts (read/write)
  • crm.objects.companies (read/write)
  • sales-email-read

Quick Start

# 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

Docker Configuration

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"
      ]
    }
  }
}

Building Docker Image

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 .

Development

pip install -e .

License

MIT License

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