HubSpot CRM Integration
What is HubSpot CRM Integration
MCP-HubSpot is a Model Context Protocol server designed to facilitate seamless interaction between AI assistants and HubSpot CRM data. It allows AI models to access and manage contacts, companies, and engagement data within HubSpot, enhanced with vector storage and caching capabilities to address API limitations.
Use cases
Users can leverage MCP-HubSpot to automate CRM tasks, such as creating contacts and companies from external data sources, retrieving real-time insights on pipeline status, and performing semantic searches across historical data interactions—all of which enhance productivity and streamline workflows.
How to use
To get started, obtain a HubSpot access token with the necessary scopes, and deploy the server using Docker. You can run the server directly or configure it within a client application. The setup is designed to be simple, allowing for quick integration with existing workflows.
Key features
MCP-HubSpot features include efficient vector storage using FAISS for fast semantic search, thread-level indexing for precise retrieval of conversation data, and embedding caching to optimize processing. The server supports persistent storage to maintain data across sessions and is built for multi-platform compatibility.
Where to use
MCP-HubSpot can be utilized in any environment where AI assistants are integrated into CRM workflows. It is particularly beneficial for sales teams, customer service applications, and any business operations focused on leveraging AI for enhanced CRM engagement and management.
Overview
What is HubSpot CRM Integration
MCP-HubSpot is a Model Context Protocol server designed to facilitate seamless interaction between AI assistants and HubSpot CRM data. It allows AI models to access and manage contacts, companies, and engagement data within HubSpot, enhanced with vector storage and caching capabilities to address API limitations.
Use cases
Users can leverage MCP-HubSpot to automate CRM tasks, such as creating contacts and companies from external data sources, retrieving real-time insights on pipeline status, and performing semantic searches across historical data interactions—all of which enhance productivity and streamline workflows.
How to use
To get started, obtain a HubSpot access token with the necessary scopes, and deploy the server using Docker. You can run the server directly or configure it within a client application. The setup is designed to be simple, allowing for quick integration with existing workflows.
Key features
MCP-HubSpot features include efficient vector storage using FAISS for fast semantic search, thread-level indexing for precise retrieval of conversation data, and embedding caching to optimize processing. The server supports persistent storage to maintain data across sessions and is built for multi-platform compatibility.
Where to use
MCP-HubSpot can be utilized in any environment where AI assistants are integrated into CRM workflows. It is particularly beneficial for sales teams, customer service applications, and any business operations focused on leveraging AI for enhanced CRM engagement and management.
Content
HubSpot MCP Server
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:
| 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 |
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:
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