HubSpot MCP Server
The HubSpot MCP Server enables AI assistants to directly interact with HubSpot CRM data without intermediaries. You can:
Retrieve data: Fetch contacts, companies, recent activity history, and conversation threads
Create data: Add new contacts and companies with duplicate prevention
Search capabilities: Perform semantic searches across previously retrieved HubSpot data using FAISS vector storage
Efficiency features: Utilize SentenceTransformer with automatic embedding caching and configure persistent storage between sessions
Provides integration with HubSpot CRM, enabling AI models to interact with HubSpot data including contacts, companies, and engagements. Offers tools for retrieving, creating, and managing HubSpot objects, as well as accessing recent engagement history.
Click on "Deploy 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., "@HubSpot MCP Server create a contact for John Doe from his LinkedIn profile"
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.
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.
Related MCP server: HubSpot MCP Server
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 |
| Create contacts with duplicate prevention |
| Create companies with duplicate prevention |
| Retrieve activity for specific companies |
| Retrieve most recently active companies |
| Retrieve most recently active contacts |
| Retrieve recent conversation threads with messages |
| 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:latestDocker 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
Available Tools
16 toolshubspot_create_companyC
Create a new company in HubSpot
Inputs: name (required), properties.
hubspot_create_contactC
Create a new contact in HubSpot
Inputs: lastname (required), firstname (required), email, properties.
hubspot_create_propertyB
Create a new custom property in HubSpot
Inputs: name (required), type (required), label (required), fieldType (required), +4 more.
hubspot_get_active_companiesB
Get most recently active companies from HubSpot
Inputs: limit.
hubspot_get_active_contactsB
Get most recently active contacts from HubSpot
Inputs: limit.
hubspot_get_companyB
Get a specific company by ID from HubSpot
Inputs: company_id (required), properties.
hubspot_get_company_activityC
Get activity history for a specific company
Inputs: company_id (required).
hubspot_get_contactC
Get a specific contact by ID from HubSpot
Inputs: contact_id (required), properties.
hubspot_get_propertyB
Get details of a specific HubSpot property definition
Inputs: object_type (required), property_name (required).
hubspot_get_recent_conversationsB
Get recent conversation threads from HubSpot with their messages
Inputs: after, limit, refresh_cache.
hubspot_get_ticket_conversation_threadsB
Get conversation threads associated with a specific ticket
Inputs: ticket_id (required).
hubspot_get_ticketsC
Get tickets from HubSpot based on configurable selection criteria
Inputs: limit, criteria, max_retries, retry_delay.
hubspot_search_dataB
Search for similar data in stored HubSpot API responses
Inputs: query (required), limit.
hubspot_update_companyC
Update an existing company record in HubSpot
Inputs: company_id (required), properties (required).
hubspot_update_contactB
Update an existing contact record in HubSpot
Inputs: contact_id (required), properties (required).
hubspot_update_propertyB
Update a HubSpot property definition (e.g., add dropdown options)
Inputs: options (required), object_type (required), property_name (required).
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 16 tools
Most tools have distinct purposes (companies, contacts, properties, tickets, conversations), but 'hubspot_search_data' is vague and overlaps with the broader search concept, and 'get_active_companies' vs 'get_company' could cause confusion.
All tools follow a consistent 'hubspot_verb_noun' pattern in snake_case, making the naming predictable and easy to follow.
16 tools cover several CRM entities (companies, contacts, properties, tickets, conversations). The count is reasonable but slightly on the higher end for the breadth of operations provided.
While many core operations exist (create, get, update for companies/contacts/properties, get tickets), there are notable gaps: no delete operations, no ticket creation or update, no conversation creation, and missing ticket update.
Maintenance
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