Giggal.ai

io.github.hassaanali723由 GitHub 帳號 hassaanali723 發布v0.2.0更新於 Oct 24, 2026

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

已驗證Streamable HTTP可網頁執行溝通與協作商業與電商

概覽

AI 產生的概覽

Giggal.ai 讓 AI 助理驗證電子郵件地址,包含 catch-all、accept-all 與受 SEG 保護的信箱。

可以做什麼
  • 驗證單一地址或整份清單,回傳明確的可用或不可用結果,涵蓋其他工具放棄的 catch-all 與 accept-all 網域
  • 取得某次驗證工作的完整明細:每個地址的狀態、原因代碼與可投遞性評分
  • 在大量驗證前查詢剩餘驗證額度
適用情境
適合在清理或篩選郵件清單時,讓助理檢查那些被其他驗證工具標為「有風險」或「未知」的難判地址,例如 catch-all 網域或位於郵件安全閘道後方的信箱。
執行需求
遠端端點 mcp.giggal.ai,使用 streamable HTTP;Claude 與 ChatGPT 透過 OAuth 登入,IDE 與命令列用戶端需使用 Giggal.ai 開發者 API 金鑰並以 Bearer 權杖傳送。免費帳號提供 1,000 次驗證額度。自行架設的 stdio 版本需要 Node.js 或 Docker,並設定 GIGGAL_API_KEY 環境變數。
安裝前請注意
需要 Giggal.ai 帳號並授權 verify:read 權限,或使用需妥善保管的 API 金鑰。免費額度用完後驗證會消耗付費額度。送出驗證的電子郵件地址會傳送至 Giggal.ai 的 API。所列工具為唯讀,但驗證結果屬第三方判斷,並非保證。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 Giggal.ai,將其新增到工作區。
  2. 連接 所需的 憑證。它們會被私密儲存,絕不會在公開頁面上展示。
  3. 為需要使用其工具的對話啟用該服務。

Web executable,透過 Streamable HTTP。 遠端服務在工作區中設定後即可從網頁執行環境執行。

交給代理程式安裝

把這段提示詞貼上到 Claude Code、Codex、Cursor 等代理程式,或 SourceWeft 對話中。代理程式會讀取該伺服器的安裝指南,先向你展示發布者、端點和登入方式,經你同意後再把它新增到你的客戶端。金鑰不會寫進任何命令。

閱讀 https://sourceweft.com/mcp/io.github.hassaanali723%2Fgiggal-mcp/install.md,並按其中說明把這個 MCP 伺服器接入我的客戶端。修改任何設定之前,先告訴我它的發布者、端點和登入方式,等我確認。不要把 API 金鑰寫進命令或我會提交的檔案;問我金鑰應從哪裡取得。

檢視代理程式所依據的安裝指南

其他 MCP 客戶端

把它新增到你客戶端的 mcpServers 設定中。 客戶端會在首次連接時完成 OAuth 登入。

{
  "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.

來源:README.md,提交 f4d6da0

工具

0
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版本歷史

1
  1. v0.2.0最新Sep 16, 2026

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