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官方说明3 个来源MCP 服务3 天前
baryhuang/mcp-hubspot

baryhuang/mcp-hubspot

HubSpot CRM integration for AI assistants
在 GitHub 查看 ↗直链 · 无中转页
来源明细
收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-14 · 最近见到 2026-10-16 · 共见到 4 次 · 被 3 个来源列出
评分构成
综合分 303 · 3 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-10-14;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

HubSpot MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

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
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
来源
awesome · https://github.com/baryhuang/mcp-hubspot
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