HubSpot MCP Server
HubSpot MCP Server
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概述
一个 Model Context Protocol (MCP) 服务器,使 AI 助手能够与 HubSpot CRM 数据交互。该服务器将 AI 模型与您的 HubSpot 账户连接起来,提供对联系人、公司和互动数据的直接访问。内置的向量存储和缓存机制有助于克服 HubSpot API 的限制,同时缩短响应时间。
我们的实现优先处理最常用、高价值的 HubSpot 操作,并具备稳健的错误处理和 API 稳定性。每个组件都针对 AI 友好交互进行了优化,确保即使在复杂的多步骤 CRM 工作流中也能保持可靠性能。
Related MCP server: HubSpot MCP Server
为什么选择 MCP-HubSpot?
直接 CRM 访问:将 Claude 和其他 AI 助手直接连接到您的 HubSpot 数据,无需中间步骤
上下文保留:使用 FAISS 的向量存储支持对先前交互进行语义搜索
零配置:简单的 Docker 部署,设置极少
示例提示词
Create HubSpot contacts and companies from this LinkedIn profile:
[Paste LinkedIn profile text]What's happening lately with my pipeline?可用工具
该服务器提供用于 HubSpot 管理和数据检索的工具:
工具 | 用途 |
| 创建联系人并防止重复 |
| 创建公司并防止重复 |
| 检索特定公司的活动 |
| 检索最近活跃的公司 |
| 检索最近活跃的联系人 |
| 检索带有消息的最近对话线程 |
| 对先前检索的 HubSpot 数据进行语义搜索 |
性能特性
向量存储:利用 FAISS 进行高效的语义搜索和检索
线程级索引:单独存储每个对话线程,以实现精确检索
嵌入缓存:使用带有自动缓存的 SentenceTransformer
持久化存储:数据在会话之间持久保存于可配置的存储目录中
多平台支持:针对多种架构优化的 Docker 镜像
设置
先决条件
您需要一个具有以下范围的 HubSpot 访问令牌:
crm.objects.contacts(读/写)
crm.objects.companies(读/写)
sales-email-read
Docker 配置
用于在 Claude desktop 中进行手动配置:
{
"mcpServers": {
"hubspot": {
"command": "docker",
"args": [
"run", "-i", "--rm",
"-e", "HUBSPOT_ACCESS_TOKEN=your_token",
"-v", "/path/to/storage:/storage", # Optional persistent storage
"dennis/mcp-hubspot:latest"
]
}
}
}构建 Docker 镜像
要在本地构建 Docker 镜像:
git clone https://github.com/dennis19741216/AI-assistant-with-HubSpot-CRM.git
cd mcp-hubspot
docker build -t mcp-hubspot .对于多平台构建:
docker buildx create --use
docker buildx build --platform linux/amd64,linux/arm64 -t dennis/mcp-hubspot:latest --push .开发
pip install -e .This server cannot be installed
Maintenance
Resources
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If you are the server author, to access and configure the admin panel.
Related MCP Servers
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- AlicenseNot gradedqualityDmaintenanceEnables AI assistants to interact with HubSpot CRM for managing contacts, companies, deals, and sending emails through natural language commands.182MIT
- AlicenseAqualityBmaintenanceExposes HubSpot CRM data and actions as tools for AI agents, enabling contact lookup, company search, contact creation, and activity logging via natural language.4182MIT
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