chat-gun MCP Server
HsienW/chat-gun
[](https://agentrank-ai.com/tool/HsienW--chat-gun/?utm_source=badge&utm_medium=readme&utm_campaign=agentrank_badge) 🤖 A full-stack Agent Chat Runtime for pre-production validation, built with act, TypeScript, and LangGraph JS combining streaming, multimodal, HITL, and tools with durable Task/Step execution, retry budgets, idempotency, compensation, distributed locks, context governance, OpenTelemetry tracing, model fallback, cost tracking, and Opik evaluation.
claude mcp add agentrank -- npx -y agentrank-mcp-server Overview
HsienW/chat-gun is a TypeScript tool. 🤖 A full-stack Agent Chat Runtime for pre-production validation, built with act, TypeScript, and LangGraph JS combining streaming, multimodal, HITL, and tools with durable Task/Step execution, retry budgets, idempotency, compensation, distributed locks, context governance, OpenTelemetry tracing, model fallback, cost tracking, and Opik evaluation. Topics: agent, chatbot, langgraph, multi-agent, qwen, mcp, ai-agent.
Ranked #2820 out of 24846 indexed tools.
Ecosystem
Score Breakdown
143 stars → growing community
Last commit 1mo ago → recently updated
28/35 issues closed → responsive maintainer
1 contributor → solo project
No dependents → no downstream usage
Weights: Freshness 20% · Issue Health 20% · Dependents 22% · Stars 10% · Contributors 8% · How we score →
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From the README
# Chat Gun <p align="center"> </p> <p align="center"> <a href="./README.en.md">English</a> | <a href="./README.md">繁體中文</a> | <a href="./README.zh-CN.md">简体中文</a> </p> Chat Gun 是一套以 React、TypeScript 與 LangGraph JS 建構的全端 Agent Chat 應用。它支援多 Agent 對話、串流回覆、Tool Calling、圖片輸入與 Human-in-the-Loop,並透過 BFF 統一處理瀏覽器與 LangGraph Runtime 之間的 API 流量。 ## 核心功能 - **Agent-workflows**: - Deep Researcher 負責多步驟研究與引用驗證。 - Chat Assistant 處理一般對話。 - Math Solver 執行算式與數值運算。 - MCP Agent 則透過 Tool Calling 使用 native 與 MCP tools。 - **Streaming**:即時串流回答與執行活動,並支援 Cancellation 與 Exception handling,讓使用者能中止進行中的請求並看見明確的錯誤狀態。 - **HITL**:天氣地點不明確時,Agent 會列出候選地點向使用者確認,再接續原本的 thread 執行。 - **Multimodal input**:接受 PNG、JPEG 與 WebP 圖片,透過 vision model 分析內容並納入回答或研究流程。 - **Native Tools**:內建計算、由 Tavily Search API 提供的網路搜尋、網頁擷取、目前天氣與天氣預報工具,Agent 可依問題選擇合適工具。 - **MCP integration**:可選擇載入 Filesystem 與 Brave Search MCP Server;Brave Search 以選配 MCP Tool 的形式擴充搜尋能力。 - **Model providers**:支援 Qwen、OpenAI-compatible 與 CCR-compatiRead full README on GitHub →
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