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Hubspot Mcp Server

Hubspot Mcp Server

Local
github.com/DidelotKData & Analytics0Updated 70w ago

About Hubspot Mcp Server

Hubspot Mcp Server connects MCP clients to HubSpot data and deal operations. It combines entity browsing and filtering with semantic search and caching tools.

Key features

  1. 01Browse contacts, companies, deals, and engagements
  2. 02Search entities with filters
  3. 03Read entity properties and schemas
  4. 04Create and update deals
  5. 05Semantic search with FAISS
  6. 06Cache and bulk-load entities

Use cases

  1. 01Find HubSpot records using natural-language queries
  2. 02Review deal details and update deal records
  3. 03Explore available fields for HubSpot entities

MCP support

An MCP server exposing 18 tools for HubSpot contacts, companies, deals, and engagements, including search, deal management, semantic search, and cache operations.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

HubSpot MCP Server

Semantic Release Conventional Commits

MCP (Model Context Protocol) server for integrating HubSpot with MCP clients (like Claude Desktop). Provides access to HubSpot contacts, companies, and deals through conversational tools.

🛠️ Available Tools

The server provides 18 tools for comprehensive HubSpot integration:

CategoryToolsDescription
📋 Entity Listinglist_hubspot_contacts
list_hubspot_companies
list_hubspot_deals
list_hubspot_engagements
List and browse HubSpot entities with pagination support
🔧 Propertiesget_hubspot_contact_properties
get_hubspot_company_properties
get_hubspot_deal_properties
Retrieve field properties and schemas for each entity type
🔍 Search & Filteringsearch_hubspot_contacts
search_hubspot_companies
search_hubspot_deals
Advanced search with filters for each entity type
💼 Deal Managementget_deal_by_name
create_deal
update_deal
Complete deal lifecycle management
🤖 AI-Powered Searchsemantic_search_hubspot
manage_hubspot_embeddings
browse_hubspot_indexed_data
Semantic search using natural language with FAISS vector database
⚡ Cache & Performanceload_hubspot_entities_to_cache
manage_hubspot_cache
Bulk loading, caching, and performance optimization

A complete documentation of the tools can be found here : Tools documentation


⚡ Usage Examples

Once fully installed and configured (following the complete installation guides), use natural language phrases with your MCP client:

🗣️ Natural Language Queries
  • "List my HubSpot contacts"
  • "Find tech sector companies"
  • "Show current deals"
  • "Create a new deal for Project X"
  • "Search for the 'Project X' deal"
  • "What contact properties are available?"
🤖 AI-Powered Semantic Search
  • "Find software engineers" → matches "Developer", "Programmer", "Software Architect"
  • "Search for enterprise clients" → finds large companies without exact keywords
  • "Technology companies in Paris" → contextual location and industry search

A complete documentation of the differents usage can be found here : Usage examples


📚 Documentation Table of Contents

🚀 Getting Started
SectionDescription
Client IntegrationComplete Guide for MCP Client Integration
Claude Desktop IntegrationComplete guide for stdio and SSE modes with Claude Desktop
🔧 Extra Features
SectionDescription
Semantic SearchAI-powered semantic search capabilities and usage
Cache SystemHow the shared TTL cache works and how to manage it
SSE EndpointsREST API endpoints for health monitoring and data management
🛠️ Development and Testing
SectionDescription
Developer GuideTesting, quality assurance, and development workflow
MCP InspectorVisual debugging and testing with MCP Inspector
TroubleshootingCommon issues and solutions
Integration TestingComprehensive testing procedures
Local Installation (stdio)Install and run locally
Remote Deployment (SSE)Deploy to Kubernetes for production use
Environment SetupAdvanced environment configuration

📋 Quality Assurance: Pre-commit hooks ensure automatic code formatting, documentation linting, and broken link checking on every commit. Install with just install-dev.


🤝 Contributing

Check the contributing guide for:

  • Development standards
  • Tool creation process
  • Code and testing conventions
  • Git workflow and semantic versioning

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.