Codify MCP

MCP server for custom automation tools using Apify Agent

Part of Project Codify

Project Codify

Complete end-to-end browser automation pipeline running inside browser (or locally). Codify and replay browser actions as robust (deterministic) and reusable scripts. From rapid prototyping and quick automation scripts to sophisticated deployments at scale.

• Login - reusable authentication sessions - reusable secure login (TBD) ❎

• Agent - turn scripts into browser actions - code or text script (future) ✅

• Coder - turn browser actions into scripts (TBD - currently integrated) ✅

• Robot - automation engine for scalability (TBD - currently integrated) ✅

• MCP - automations become reusable tools you can reuse through AI ✅

More is on the way... Give it a shot 🎬 or join the list to follow the project! 🔔

What It Does

Model Context Protocol (MCP) server that lets AI assistants (e.g. Claude, Cursor, VS Code) execute browser automation tasks via Apify Agent. Tools are passed as clean JSON arguments — one per line. No manual setup or file creation.

Usage

Run directly using npx:

npx codify-mcp {{JSON_MCP_TOOL_1}} {{JSON_MCP_TOOL_2}} {{JSON_MCP_TOOL_3}}...

Or install locally:

npm install -g codify-mcp

Quick Start

1. Apify Token

Optional - you can also place the token inside the MCP server JSON later.

apify login

This saves your token to ~/.apify/auth.json.

Alternatively, set the environment variable:

export APIFY_TOKEN="your_token_here"

2. Create a Tool

Apify Coder can turn casual browser actions into reusable AI tools. Currently, this feature is also integrated in Apify Agent

Export a tool and append the result as a JSON string to the MCP server args field or ask your AI to do it for you.

{
  "name": "scrape_product",
  "description": "Scrape product info from a page",
  "inputSchema": {
    "type": "object",
    "properties": {
      "url": {
        "type": "string",
        "description": "Product page URL"
      }
    },
    "required": ["url"]
  },
  "implementation": {
    "type": "apify-actor",
    "actorId": "cyberfly/apify-agent",
    "script": "await page.goto(inputs.url); const title = await page.textContent('h1'); return {title};"
  }
}

3. Run the Server

npx codify-mcp '{"name":"scrape_product","description":"...","inputSchema":{...},"implementation":{...}}'

Or with multiple tools:

npx codify-mcp \
  '{"name":"tool1",...}' \
  '{"name":"tool2",...}' \
  '{"name":"tool3",...}'

4. Connect to Claude Desktop (or Cursor/VS Code)

Edit your Claude Desktop config:

macOS/Linux: ~/.config/Claude/claude_desktop_config.json

Windows: %APPDATA%\Claude\claude_desktop_config.json

{
  "mcpServers": {
    "codify-mcp": {
      "command": "npx",
      "args": [
        "codify-mcp",
        "{\"name\":\"scrape_product\",\"description\":\"...\",\"inputSchema\":{...},\"implementation\":{...}}"
      ],
      "env": {
        "APIFY_TOKEN": "your_token_or_leave_empty_to_use_auth_file"
      }
    }
  }
}

Restart Claude. Your tools are now available to the AI assistant.

Tool Definition Reference

Basic Structure

{
  // Required
  "name": "tool_name",                    // alphanumeric + underscore/dash
  "description": "What the tool does",    // shown to AI
  "inputSchema": {
    "type": "object",
    "properties": {
      "paramName": {
        "type": "string",
        "description": "Parameter description"
      }
    },
    "required": ["paramName"]
  },
  "implementation": {
    "type": "apify-a

... [View full README on GitHub](https://github.com/cybairfly/codify-mcp#readme)