GitHub
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
Description from the maker (original English)
Code review by AI models from different companies, usually two. Shows where they agree and disagree.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
AuthorizationValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Run this in your terminal
claude mcp add --transport http megalens https://megalens.ai/api/mcp --header 'Authorization: your-value'Fill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"megalens": {
"url": "https://megalens.ai/api/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"megalens": {
"type": "http",
"url": "https://megalens.ai/api/mcp",
"headers": {
"Authorization": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.
Your choice stays on this device in a cookie; no account needed.
Authorization secret required HTTP headerThese settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
We have not read this server’s tool list yet; we check endpoints in rotation.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified against the domain megalens.ai (the registry checks domain ownership)
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
Not checked yet; we check endpoints in rotation
Not checked yet; we check endpoints in rotation
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: Authorization
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
The GitHub repo last changed –, and the latest version (1.0.0) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: GitHub, Desktop Commander, Cloudflare MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
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: