Giggal.ai

io.github.hassaanali723Published by GitHub account hassaanali723v0.2.0Updated Oct 24, 2026

Runs a deep mailbox existence check to verify catch-all, accept-all, and SEG protected emails.

VerifiedStreamable HTTPWeb executableCommunication & CollaborationBusiness & Commerce

Overview

AI-generated overview

Giggal.ai verifies email addresses, including catch-all, accept-all and SEG-protected mailboxes, from inside an AI assistant.

What you can do
  • Verify a single address or a whole list and get a clear valid or invalid result, including catch-all and accept-all domains
  • Fetch the full breakdown for a verification job: per-address status, reason codes and deliverability scoring
  • Check remaining verification credits before a large run
When to use it
Useful when cleaning or qualifying email lists and you want the assistant to check deliverability of hard addresses that other verifiers mark as risky or unknown, such as catch-all domains or inboxes behind email security gateways.
Requirements
Remote endpoint at mcp.giggal.ai over streamable HTTP; OAuth sign-in for Claude and ChatGPT, or a Giggal.ai Developer API key sent as a Bearer token for IDE and CLI clients. A free account provides 1,000 verification credits. A self-hosted stdio variant needs Node.js or Docker and the GIGGAL_API_KEY environment variable.
Before you install
Requires a Giggal.ai account and OAuth grant of the verify:read scope, or an API key that must be kept secret. Verification consumes paid credits once the free allowance is used. Addresses submitted for verification are sent to Giggal.ai's API. The listed tools are read only, but verification results are third-party judgments, not guarantees.

Installation

In SourceWeft

  1. Open Giggal.ai in the dashboard and add it to a workspace.
  2. Connect the required credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.hassaanali723%2Fgiggal-mcp/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config. The client completes OAuth sign-in on first connect.

{
  "mcpServers": {
    "giggal-ai": {
      "type": "http",
      "url": "https://mcp.giggal.ai/mcp"
    }
  }
}

README

Giggal.ai MCP Server

Available on Smithery

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

bash
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)
json
{  "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:

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

Zed

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

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

Codex

Add to ~/.codex/config.toml:

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:

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

Restart the client after adding, then just ask:

Is [email protected] deliverable?

Tools

ToolWhat it does
verify_emailsVerify a single address or a whole list and get a clear valid or invalid result, including catch-all and accept-all domains other tools give up on
get_verification_detailsFetch the full breakdown for a job: per-address status, reason codes, and deliverability scoring
get_credit_balanceCheck remaining verification credits before a large run

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:

bash
npm installnpm run buildGIGGAL_API_KEY=tp_live_... npm run start:local

With Docker:

bash
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):

json
{  "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.

For REST API examples in JavaScript and Python, see the Giggal.ai email verifier developer hub.

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.

Source: README.md at commit f4d6da0

Tools

0
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Version history

1
  1. v0.2.0LatestSep 16, 2026

Score

85% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listed15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts