Giggal MCP Server

Giggal.ai MCP Server

Verify catch-all, accept-all, and SEG-protected email addresses without leaving Claude, ChatGPT, Cursor, VS Code, or any other MCP client. This is the official Model Context Protocol server for Giggal.ai, the catch-all email verification tool that confirms the mailboxes other verifiers write off as "risky" or "unknown."

MCP URL:  https://mcp.giggal.ai/mcp

Why Giggal.ai

Most tools give up on the hard addresses. Giggal.ai runs a deep mailbox existence check over SMTP and returns a real deliverability result where others cannot:

• Catch-all and accept-all domains that accept every address, even for users who do not exist
• SEG-protected inboxes behind Proofpoint, Mimecast, and Barracuda that block the checks most verifiers rely on
• Risky B2B contacts that competitors flag and discard, around 30% of a typical list, recovered as deliverable

99% accuracy on standard business lists and bounce rates under 3%, straight from your AI assistant.

Get an API key

Sign up at emailverifier.giggal.ai for 1,000 free verification credits, no card required, then copy your key from the Developer API tab. Claude and ChatGPT connect over OAuth and need no key. The IDE and CLI clients below use the key as a Bearer token.

Connect your AI client

Claude

Add Giggal.ai as a custom connector. No config files, no API key.

1. Open Settings → Connectors (web or desktop).
2. Click Add → Add custom connector.
3. Name it Giggal.ai, paste the MCP URL, then click Add.
4. Open the Giggal.ai connector and click Connect.
5. Click Allow to grant verify:read (verify addresses, check credits, look up past verifications).

ChatGPT

Add Giggal.ai as a custom plugin, connected over OAuth.

1. Open Plugins from the sidebar, then click the + in the top right.
2. Name it Giggal.ai, set Server URL to the MCP URL, choose Authentication → OAuth, tick the confirmation, then click Create.
3. Open the plugin, click Connect, then Sign in with Giggal.ai.
4. Click Allow to grant verify:read.

Claude Code

claude mcp add --transport http --scope user giggal \
  https://mcp.giggal.ai/mcp \
  --header "Authorization: Bearer YOUR_API_KEY"

Already have a giggal server? Run claude mcp remove giggal --scope user first, then re-add.

Cursor, Windsurf, and Cline

Add this to your MCP config file:

• Cursor: ~/.cursor/mcp.json (or .cursor/mcp.json per project)
• Windsurf: ~/.codeium/windsurf/mcp_config.json
• Cline: cline_mcp_settings.json (open it from the Cline MCP settings)

{
  "mcpServers": {
    "giggal": {
      "url": "https://mcp.giggal.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

VS Code

Add to .vscode/mcp.json. VS Code uses servers instead of mcpServers:

{
  "servers": {
    "giggal": {
      "url": "https://mcp.giggal.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Zed

Add to ~/.config/zed/settings.json:

{
  "context_servers": {
    "giggal": {
      "source": "custom",
      "url": "https://mcp.giggal.ai/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Codex

Add to ~/.codex/config.toml:

[mcp_servers.giggal]
url = "https://mcp.giggal.ai/mcp"
bearer_token_env_var = "GIGGAL_API_KEY"

Codex reads the key from an env var. Set it and reload your shell, then fully quit and reopen Codex:

echo 'export GIGGAL_API_KEY="tp_live_..."' >> ~/.zshrc
source ~/.zshrc

---

Restart the client after adding, then just ask:

Is info@giggal.ai deliverable?

Tools

All tools are read only.

What this service does

• Speaks the Model Context Protocol so AI assistants can call the tools above
• Serves an OpenAPI 3.1 spec so ChatGPT Custom GPTs (GPT Actions) can use it
• Runs an OAuth 2.1 authorization server so AI clients can authenticate users
• Wraps the Giggal.ai verification API and never re-implements verification logic

Run it locally (self-host)

Prefer to run your own instance instead of the hosted server? The giggal-mcp command is a small stdio server that calls the public Giggal.ai API with your own Developer API key. No database, no OAuth, nothing to host.

From source:

npm install
npm run build
GIGGAL_API_KEY=tp_live_... npm run start:local

With Docker:

docker build -t giggal-mcp .
docker run -i --rm -e GIGGAL_API_KEY=tp_live_... giggal-mcp

In an MCP client (point it at your locally built copy):

{
  "mcpServers": {
    "giggal": {
      "command": "node",
      "args": ["/path/to/giggal-mcp/dist/local/index.js"],
      "env": { "GIGGAL_API_KEY": "tp_live_..." }
    }
  }
}

Same three tools as the hosted server. GIGGAL_API_BASE optionally overrides the API base (defaults to https://api.giggal.ai/v1).

About this repository

This repo powers both the hosted server at https://mcp.giggal.ai/mcp (OAuth, zero setup) and the local stdio server above (giggal-mcp, your own API key). Both expose the same three tools and call the Giggal.ai verification API to do the actual work. It is published for transparency.

Endpoints

The hosted server exposes:

• POST /mcp MCP JSON-RPC (main protocol endpoint)
• GET /mcp MCP SSE stream (server to client notifications)
• GET /openapi.json OpenAPI 3.1 spec (for GPT Actions)
• POST /oauth/register Dynamic Client Registration (RFC 7591)
• GET /oauth/authorize User consent screen
• POST /oauth/token Access token exchange
• POST /oauth/revoke Revoke a token
• GET /.well-known/oauth-authorization-server Server metadata
• GET /health Health check

License

MIT. See LICENSE.