Giggal
Giggal.ai is an email verification tool that runs a deep mailbox existence check on every address and verifies catch-all/accept-all and even SEG protected emails. Your bounce rate stays under 5%, and the 30% of every B2B list that other tools flag as "Risky" becomes deliverable again.
README
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.
- Open Settings → Connectors (web or desktop).
- Click Add → Add custom connector.
- Name it Giggal.ai, paste the MCP URL, then click Add.
- Open the Giggal.ai connector and click Connect.
- 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.
- Open Plugins from the sidebar, then click the + in the top right.
- Name it Giggal.ai, set Server URL to the MCP URL, choose Authentication → OAuth, tick the confirmation, then click Create.
- Open the plugin, click Connect, then Sign in with Giggal.ai.
- 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.jsonper 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
| Tool | What it does |
|---|---|
verify_emails |
Verify 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_details |
Fetch the full breakdown for a job: per-address status, reason codes, and deliverability scoring |
get_credit_balance |
Check 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:
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 /mcpMCP JSON-RPC (main protocol endpoint)GET /mcpMCP SSE stream (server to client notifications)GET /openapi.jsonOpenAPI 3.1 spec (for GPT Actions)POST /oauth/registerDynamic Client Registration (RFC 7591)GET /oauth/authorizeUser consent screenPOST /oauth/tokenAccess token exchangePOST /oauth/revokeRevoke a tokenGET /.well-known/oauth-authorization-serverServer metadataGET /healthHealth check
License
MIT. See LICENSE.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。