Charles-mcp — MCP Server by heizaheiza

by heizaheiza · MCP Server · ★ 264

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About Charles-mcp

Charles MCP Server English README Agent Workflows Charles MCP Server 用于把 Charles Proxy 接入 MCP 客户端,让 agent 可以稳定地读取实时流量、分析历史录包,并在需要时再展开单条请求细节。 它解决的核心问题只有三个: 录制还在进行时,agent 也能持续读取当前 session 的增量流量 live 与 history 统一走结构化分析,不再让 agent 直接消费原始抓包字典 默认使用 summary-first 输出,先看热点与摘要,再 drill-down 到单条 detail 本次更新方向(v3.0) 的更新方向是: 的能力开始从“流量查看/筛选”向“逆向工程工作流”延伸。 在保留原有 live/history 分析能力的基础上,新增 reverse-analysis 工具链(导入、查询、解码、回放、签名候选分析、live 逆向会话)。 目标是让 agent 不只看到流量,还能围绕认证、签名、参数变异与可重放性,形成更完整的逆向分析闭环。 快速开始 开启 Charles Web Interface 在 Charles 中依次进入: 请确认: 勾选 用户名为 密码为 菜单位置示意: 设置窗口示意: 安装并配置到 MCP 客户端 无需 clone 仓库,无需手动创建虚拟环境。需要先安装 uv。 Claude Code CLI bash claude mcp add-json charles '{ "type": "stdio", "command": "uvx", "args": ["charles-mcp"], "env": {

ai-agentcharles-proxycodexdeveloper-toolsmcpmcp-servernetwork-debuggingopenai

Quick Facts

Stars264
Forks27
LanguagePython
CategoryMCP Server
LicenseMIT
Quality Score71.0681681693634/100
Open Issues1
Last Updated2026-06-23
Created2026-03-06
Platformscodex, mcp, python
Est. Tokens~17k

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Frequently Asked Questions

What is Charles-mcp?

Charles-mcp is Charles Proxy MCP server for AI agents with live capture, structured traffic analysis, and agent-friendly tool contracts. It is categorized as a MCP Server with 264 GitHub stars.

What programming language is Charles-mcp written in?

Charles-mcp is primarily written in Python. It covers topics such as ai-agent, charles-proxy, codex.

How do I install or use Charles-mcp?

You can find installation instructions and usage details in the Charles-mcp GitHub repository at github.com/heizaheiza/Charles-mcp. The project has 264 stars and 27 forks, indicating an active community.

What license does Charles-mcp use?

Charles-mcp is released under the MIT license, making it free to use and modify according to the license terms.

What are the best alternatives to Charles-mcp?

The top alternatives to Charles-mcp on Agent Skills Hub include Overture, wcgw, Mantic.sh. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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