Other MCP Server · MODEL CONTEXT PROTOCOL
larryfang sms mcp
larryfang sms mcp is a community-listed Model Context Protocol server. Review the source repository before installation.
连接能力
larryfang sms mcp 为 AI Agent 提供什么
来源目录未提供结构化功能列表,请在使用前阅读源仓库文档。
安全
MCP 收录不等于安全审核
MCP 服务器可能获得模型上下文、凭据、本地文件或调用外部系统的权限。连接 Agent 前,请检查代码、环境变量、网络行为、软件包来源与维护状态。
README
仓库文档
An AI-native SMS assistant powered by GPT and MessageMedia — now with a live SMS report dashboard!
- Send and receive SMS via GPT
- View full SMS conversation history
- Auto-reply via GPT using webhook
- Contextual memory per phone number
- MCP-compliant with
/metaand/function-schema - LangChain agent integration
- 📊 Live SMS Report Dashboard (NEW!)
Below is a screenshot of the embedded high bar chart showing SMS volume:
User ↔ chat.html
↕
GPT Chat Server (OpenAI-router.js)
↕ (tool calls)
MCP Server (index.js)
↕
MessageMedia SMS API
index.js: Core MCP server, webhook processor,/context+/send+/reportendpointsOpenai-router.js: ChatGPT proxy handling tool calls via OpenAI Functionschat.html: Interactive frontend for messaging and toolssms_report_live_dashboard.html: Live chart using/report
npm install
OPENAI_API_KEY=your_key node start-all.js- Access Chat UI: http://localhost:3000/chat.html
- Access Report Dashboard: http://localhost:3000/sms_report_live_dashboard.html
.
├── index.js # MCP Server
├── Openai-router.js # GPT Chat Interface
├── webhook-log.json # Legacy logs (if not using MessageMedia)
├── chat.html # GPT chat client
├── sms_report_live_dashboard.html # Dashboard with Chart.js
├── langchain_mcp_agent.py # LangChain integration script
├── .env # Environment variables
├── public/
│ └── sms_report_preview.png # Chart screenshot
-
get_sms_context -
send_sms -
show_sms_report(NEW)
- 🔄 Auto-classification of replies
- 📈 Sentiment + urgency scoring
- 🤖 Unified Copilot with webhook/CLI/chat
A new feature has been added to display a live dashboard of SMS volume by day.
You can now ask in the chat.html interface:
"Show me my report history of +61412345678"
The assistant will respond with an embedded report like this:
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