HubSpot MCP Server
About
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.
Details
- License
- MIT
Explore
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
HubSpot MCP ServerCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
You'll need a HubSpot access token with these scopes:
- crm.objects.contacts (read/write)
- crm.objects.companies (read/write)
- sales-email-read
npx -y @smithery/cli@latest install mcp-hubspot --client claude
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"
]
}
}
}
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
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 |
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"hubspot mcp server": {
"mcp-hubspot": {
"command": "npx",
"args": [
"-y",
"@smithery/cli@latest",
"install",
"mcp-hubspot",
"--client",
"claude"
]
}
}
}
}McpServers
{
"mcp-hubspot": {
"command": "npx",
"args": [
"-y",
"@smithery/cli@latest",
"install",
"mcp-hubspot",
"--client",
"claude"
]
}
}
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
```bash
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