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Avazbek22/DevProjex

Avazbek22/DevProjex

⃣ - Build token-efficient codebase co
在 GitHub 查看 ↗直链 · 无中转页
配置模板(请按你的客户端调整)
claude mcp add devprojex -- npx -y devprojex
这是根据仓库名生成的可粘贴骨架,命令行参数与包名请以该项目 README 为准。
★ 数取值
36 ★ · Avazbek22/DevProjex · 取自 GitHub 搜索 API · (2026-10-16 20:00:20 核对)
来源明细
收录自 punkpeye/awesome-mcp-servers 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-10-09 · 最近见到 2026-10-16 · 共见到 32 次 · 被 7 个来源列出
评分构成
综合分 703 · 36 ★ · 7 个来源 · mcp
常见问题(答案都来自我们的记录)
怎么安装?
我们【没有】从该仓库取到安装命令(我们的 install 覆盖率只有约 4%)。请看它的 README 或 releases 页。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
仓库 Avazbek22/DevProjex;我们收录于 2026-10-09;最近见到 2026-10-16。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。
第三方质量标记

DevProjex: MCP / GUI / CLI / TUI all in one

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

**🏆 Selected by the Avalonia UI team for the App Showcase**
**Clean, token-efficient codebase context for AI chats and coding agents. You see exactly what leaves your project, and secrets are masked before it goes.**
DevProjex turns any folder or Git repository into clean context for AI. Paste it into ChatGPT or Claude, or let Claude Code, Codex, and Cursor read the project through its read-only MCP server. A desktop app, a Terminal Workspace, a CLI, and the MCP server share one engine, one set of filters, and one masking pipeline, on Windows, macOS, and Linux.
Tick what you need in a file tree, check the live preview and its token estimate, then copy or export the result as **ASCII, Markdown, JSON, or XML**, or as a clean copy of the project in a **folder or ZIP**.
> 🔒 **Read-only and telemetry-free by design.** DevProjex does not upload your project contents or collect telemetry.
App demo 🖼️
Download 🚀
**Microsoft Store:**
👉 DevProjex
**Latest GitHub release (Windows, macOS, Linux):**
👉 github.com/Avazbek22/DevProjex/releases/latest
**WinGet (Windows):** winget install OlimoffDev.DevProjex
Run without installing
The CLI, the Terminal Workspace, and the MCP server run straight from npm or NuGet, or from a direct release binary:
The npm and NuGet packages contain the CLI, the Terminal Workspace, and the MCP server, but not the desktop app. Requirements per platform, the direct headless archives, and the non-root Docker image are all covered in Docs/Installation.md.
Why DevProjex? 💡
Copying files into a chat window one by one **doesn't scale**. Packing tools are fast, but you **see the result after it's packed**, not while you choose. And a coding agent with plain file access **reads .env as easily as Program.cs**, unless every tool it uses is told to ignore it.
DevProjex works differently: visual, precise, and local-first.
* **You see what leaves your project:** file tree, live preview, token estimate, and an agent journal that keeps a receipt of every MCP session.
* **You control what leaves it:** Smart Ignore, Git modes, secret and private-data masking, name filters, saved profiles.
* **Your agent gets the same rules:** the MCP server is read-only, secret masking there has no off switch, and with Live Context the files you tick are the agent's focus.
* **You get more than text:** a real project copy as a folder or ZIP.
The numbers, with their caveats. In the final blind series against Repomix (11 tasks, 8 repositories, 6 languages, 22 sessions per side, Claude Haiku 4.5 as the agent and as the judge), DevProjex used 973,020 tokens against 1,174,907, and the judge trusted the DevProjex answer in 17 pairs of 22 against 3. With seven planted credentials, neither tool leaked a value, but the code around them stayed readable through DevProjex in 7 files of 7 against 1 of 7. The tasks were written by the author, Repomix needs fewer tool calls, and it wins broad "how does X work" questions. The whole series, with the agents' and the judge's verdicts verbatim, is in Docs/Benchmark-History.md.
Use it for
* **AI assistants:** clean input for ChatGPT, Claude, DeepSeek, Qwen, Kimi.
* **AI agents:** any MCP client reads your project through a server that only reads and always masks, and you steer its focus with checkboxes.
* **CI pipelines:** fail a build when secrets would leak into packed context, without ever printing the values.
* **Restricted environments:** get the same clean context where AI agents, remote indexing, or IDE plugins are not allowed.
* **Large codebases:** pull out one module instead of the whole repository.
* **Code reviews and teaching:** share the structure and only the files that matter.
Get started
1. **Open or drop** a project folder.
2. **Choose** folders, files, filters, ignore rules, and output mode.
3. **Preview**, then copy, export, run the same workflow from the terminal, or connect your coding agent through **MCP → Live context**.
Works with any language, repository, or project structure.
Feature overview ✨
**Choose and control**
* **Smart Ignore:** hides build output, dependency folders, and caches, and checks for evidence before hiding anything. How it works ↓
* **Hide Secrets:** masks detected credential values where they stand, in everything you export and in every MCP response. How it works ↓
* **Hide private data:** optionally masks emails, IPs, MACs, phones, and user paths. How it works ↓
* **Code compression:** keeps declarations and signatures, empties implementation bodies; pure code gets about 3× smaller. How it works ↓
来源
awesome · https://github.com/Avazbek22/DevProjex
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