Provides visualization of SMS volume data through a live dashboard with charts displaying message history
Supports environment variable configuration for API keys and server settings
Integrates with LangChain through an agent script, allowing LangChain-based AI applications to connect to the MCP server
Integrates with OpenAI's GPT models to power AI-driven SMS responses and provide contextual conversation memory
š± Sinch MCP GPT SMS Server
An AI-native SMS assistant powered by GPT and MessageMedia ā now with a live SMS report dashboard!
ā Features
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-schemaLangChain agent integration
š Live SMS Report Dashboard (NEW!)
š Live Dashboard Preview
Below is a screenshot of the embedded high bar chart showing SMS volume:

š§ Architecture Overview
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
š ļø How to Run
Access Chat UI: http://localhost:3000/chat.html
Access Report Dashboard: http://localhost:3000/sms_report_live_dashboard.html
š Folder Structure
š¦ Tools
get_sms_contextsend_smsshow_sms_report(NEW)
š Roadmap
š Auto-classification of replies
š Sentiment + urgency scoring
š¤ Unified Copilot with webhook/CLI/chat
š SMS Report Chart
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:

This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
A full-stack SMS assistant that integrates MessageMedia SMS API with OpenAI's GPT models, enabling AI-driven SMS conversations and message management through function calling and contextual memory.
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