wais-mcp

wais-mcp

Universal MCP server for WAIS (Web Agent Interaction Standard) that provides 5 generic tools to discover, register, execute actions, confirm high-risk actions, and check status on any WAIS-compatible site.

Category
Visit Server

README

wais-mcp

Universal MCP server for WAIS (Web Agent Interaction Standard) — 5 generic tools that work with any WAIS-compatible site.

Works with Claude, ChatGPT, Gemini, Cursor, Windsurf, VS Code Copilot, and any MCP-compatible client.

Tools

Tool Description
wais_discover Fetch a site's agents.json and show available actions
wais_register Register at a site using SD-JWT selective disclosure
wais_execute Execute any action (search, subscribe, purchase, etc.)
wais_confirm Confirm high-risk actions or complete payments (402 flow)
wais_status Check account status, plan, and credits

Quick Start

pip install wais-mcp
wais-mcp init

The setup wizard will ask you to pick your provider (Claude, ChatGPT, Cursor, etc.), choose project or global scope, and enter your API key. It writes the correct config file automatically.

Manual Setup by Provider

If you prefer to configure manually, all providers use the same wais-mcp command — only the config file location and format differ.

Claude Desktop

File: claude_desktop_config.json

{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Claude Code

File: .mcp.json (project root) or ~/.claude/settings.json (global)

{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

ChatGPT Desktop

Requires Developer Mode: Settings > Advanced Settings > Developer Mode.

File locations:

  • macOS: ~/Library/Application Support/ChatGPT/mcp-server-config.json
  • Windows: %APPDATA%\OpenAI\ChatGPT\mcp-server-config.json
  • Linux: ~/.config/ChatGPT/mcp-server-config.json
{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Restart ChatGPT after saving.

Gemini CLI

File: ~/.gemini/settings.json (global) or .gemini/settings.json (project)

{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Cursor

File: .cursor/mcp.json (project) or ~/.cursor/mcp.json (global)

{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Windsurf

File: ~/.codeium/windsurf/mcp_config.json

Or open from Windsurf: click MCPs icon in Cascade panel > Configure.

{
  "mcpServers": {
    "wais": {
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

VS Code (GitHub Copilot)

File: .vscode/mcp.json (project) or via Command Palette: MCP: Open User Configuration (global)

{
  "servers": {
    "wais": {
      "type": "stdio",
      "command": "wais-mcp",
      "env": {
        "PLATFORM_URL": "https://pod.deeger.io",
        "WAIS_API_KEY": "<your-api-key>"
      }
    }
  }
}

Note: VS Code uses servers instead of mcpServers, and requires the type field.

Usage without MCP (Python SDK)

For custom agents, scripts, or any Python code — no MCP client needed:

import asyncio
from wais_mcp import WAISClient

async def main():
    client = WAISClient(api_key="your-api-key")

    # 1. Discover what the site offers
    site = await client.discover("https://serphub.deeger.io")
    print(site.name, site.list_action_ids())

    # 2. Register (shares only required claims via SD-JWT)
    await client.register(site)

    # 3. Execute actions
    result = await client.execute(site, "search", {"query": "python"})
    print(result)

    # 4. Confirm high-risk actions (if 402 returned)
    # result = await client.confirm(site, challenge_id)

    # 5. Check account status
    status = await client.status(site)
    print(status)

asyncio.run(main())

Works with OpenAI SDK, LangChain, CrewAI, or any Python agent framework.

How It Works

  1. Discover — Fetches /.well-known/agents.json from a site
  2. Register — Shares only required claims via SD-JWT selective disclosure
  3. Execute — Handles tokens, DPoP, endpoint resolution, and async polling automatically
  4. Confirm — Polls for completion after 402 confirmation challenges
  5. Status — Check credits and plan info

All authentication (PoD tokens, DPoP proofs) is handled transparently.

Configuration

Env Var Default Description
PLATFORM_URL https://pod.deeger.io WAIS Provider URL
WAIS_API_KEY (keychain fallback on macOS) API key from provider dashboard

Development

pip install -e ".[dev]"

License

MIT

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured