GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Code review by AI models from different companies, usually two. Shows where they agree and disagree.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
Authorization标为机密的值是你账户的钥匙。千万不要分享给别人,也不要粘贴到聊天里。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
在终端中运行这条命令
claude mcp add --transport http megalens https://megalens.ai/api/mcp --header 'Authorization: your-value'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"megalens": {
"url": "https://megalens.ai/api/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"megalens": {
"type": "http",
"url": "https://megalens.ai/api/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个地址需要在请求的 header 中放入密钥,而添加连接器的菜单无法设置。请改用 Claude Code、Cursor 或 VS Code。
你的选择通过 Cookie 保存在这台设备上,无需账户。
Authorization 机密 必填 HTTP header这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过域名 megalens.ai 验证(注册中心会核实域名所有权)
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
尚未检查;我们会轮流检查各个端点
尚未检查;我们会轮流检查各个端点
尚未检查;我们会在检查端点时读取工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:Authorization
它在作者的云端运行。通过互联网连接,无需安装,但你发送的内容会经过作者的服务器。
GitHub 仓库最后更新于–,最新版本(1.0.0)于2个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Code review from a panel of AI models, inside the AI tool you already use. MegaLens selects up to four AI models from different companies to review your code, and reports where they agree and where they disagree. On Free, MegaLens selects two reviewing models.
Works with Claude Code, Codex CLI, Cursor, Gemini CLI and Lovable. GitHub Copilot is coming soon.
Your first review is free, with no card.
npx megalens-mcp setup
The setup wizard:
The wizard does not ask for an OpenRouter key. To use your own key, add one header by hand: see Adding your own OpenRouter key.
| Tool | Status | Config File | Auto-detected |
|---|---|---|---|
| Claude Code | Supported | ~/.claude.json | Yes |
| Codex CLI | Supported | ~/.codex/config.toml | Yes |
| Cursor | Supported | ~/.cursor/mcp.json | Yes |
| Gemini CLI | Supported | ~/.gemini/settings.json | Yes |
| Lovable | Supported | None (a form in Lovable) | No, see below |
| GitHub Copilot (VS Code) | Coming soon, not supported yet | .vscode/mcp.json | Only if that file already exists in the folder you run the wizard from |
If no tool is detected, the wizard lets you pick one and creates the config file. The wizard can also write configs for Windsurf and Grok Build. Those are not supported or tested.
Lovable needs no config file and no wizard. Paste the server URL and your token into Lovable's MCP connector form. Steps: megalens.ai/integrations/lovable
The tools use two config languages and three different top-level keys, which is why the wizard exists.
Keep the `?ide=` on each URL. It tells MegaLens which tool the review came from. It does not change which models review your code: the panel is the same whichever tool you call it from.
Run this once. The --scope user flag makes MegaLens available in every project:
claude mcp add --transport http --scope user megalens "https://megalens.ai/api/mcp?ide=claude-code" \
--header "Authorization: Bearer ml_tok_your_token_here"
Or in .mcp.json (project) / ~/.claude.json (user):
{
"mcpServers": { "megalens": { "type": "http", "url": "https://megalens.ai/api/mcp?ide=claude-code", "headers": { "Authorization": "Bearer ml_tok_your_token_here" } } } }
~/.cursor/mcp.json or .cursor/mcp.json. No `type` field. Cursor does not use one:
{
"mcpServers": { "megalens": { "url": "https://megalens.ai/api/mcp?ide=cursor", "headers": { "Authorization": "Bearer ml_tok_your_token_here" } } } }
~/.gemini/settings.json. Gemini CLI uses httpUrl, not url:
{
"mcpServers": { "megalens": { "httpUrl": "https://megalens.ai/api/mcp?ide=gemini-cli", "headers": { "Authorization": "Bearer ml_tok_your_token_here" } } } }
GitHub Copilot is coming soon. If you want to try it early: .vscode/mcp.json. The top-level key is `servers`, not `mcpServers`. A config written for Claude Code or Cursor will not be read here:
{
"servers": { "megalens": { "type": "http", "url": "https://megalens.ai/api/mcp?ide=copilot", "headers": { "Authorization": "Bearer ml_tok_your_token_here" } } } }
~/.codex/config.toml or .codex/config.toml. TOML, not JSON:
[mcp_servers.megalens]
url = "https://megalens.ai/api/mcp?ide=codex" http_headers = { "Authorization" = "Bearer ml_tok_your_token_here" }
Add one more header alongside Authorization, in whichever shape your tool uses above. The key needs credit on it. You pay OpenRouter directly; MegaLens is not part of that bill.
"x-megalens-openrouter-key": "[PopNx MCP ตัดค่าที่หน้าตาเหมือนกุญแจออก]"
In Codex TOML:
http_headers = { "Authorization" = "Bearer ml_tok_your_token_here", "x-megalens-openrouter-key" = "[PopNx MCP ตัดค่าที่หน้าตาเหมือนกุญแจออก]" }
With Claude Code's command, add --header "x-megalens-openrouter-key: [PopNx MCP ตัดค่าที่หน้าตาเหมือนกุญแจออก]".
If you skip the key, use pay-as-you-go credits instead: $9 per 1M blended tokens, prepaid from $20.
| Command | Description |
|---|---|
megalens-mcp setup | Interactive setup: detect tools, write config |
megalens-mcp validate | Test your token connectivity |
megalens-mcp config | Show current config status |
MegaLens selects up to four AI models from different companies to review your code. They review it separately. A final check reviews their findings, and you get back where they agreed and where they disagreed. Each result names the models that actually took part.
If you send your own assessment with the request, the answer also says what the panel found that yours did not.
The panel is the same whichever tool you call it from. MegaLens reports; it does not change your code. Your own tool stays the one that decides what to do next.
Our private recipe. What stays private: how we choose the models and what each one is asked to do,
the numbers that tune each check, and the prompts. That recipe came from months of measured runs and
changes as models change. Our results, rules and mistakes are public: