slouchd/cyberchef-api-mcp-server

Overview

An MCP server that wraps the CyberChef API, exposing its data transformation operations to AI agents via the Model Context Protocol. It allows LLMs and other MCP-compatible tools to encode, decode, encrypt, decrypt, or convert data programmatically.

Best for

Best for
Developers building AI agents that need on-demand data transformation and encoding without leaving the chat interface.

Use cases

• Run base64 encoding or URL decoding through natural language prompts
• Perform AES encryption or hash computation via an AI assistant
• Convert between data formats like hex, binary, or JSON within an agent workflow

How to use

Install

CYBERCHEF_API_URL="your-cyberchef-api-url" uv run cyberchef_api_mcp_server

Tools exposed

• get_cyberchef_operations_categories
• get_cyberchef_operation_by_category
• bake_recipe
• batch_bake_recipe
• perform_magic_operation

Tested with

Claude Desktop

Example client config

{\n "mcpServers": {\n   "CyberChef API MCP Server": {\n     "command": "uv",\n     "args": [\n       "run",\n       "--with",\n       "mcp[cli]",\n       "--directory",\n       "cyberchef-api-mcp-server/cyberchef_api_mcp_server/",\n       "mcp",\n       "run",\n       "server.py"\n     ],\n     "env": {\n       "CYBERCHEF_API_URL": "your-cyberchef-api-url"\n     }\n   }\n }\n}

Notes

An MCP server that wraps the CyberChef API, exposing its data transformation operations to AI agents via the Model Context Protocol. It allows LLMs and other MCP-compatible tools to encode, decode, encrypt, decrypt, or convert data programmatically.

39 stars on GitHub. Last updated 2026-04-03. Licensed MIT.

Use cases

• Run base64 encoding or URL decoding through natural language prompts
• Perform AES encryption or hash computation via an AI assistant
• Convert between data formats like hex, binary, or JSON within an agent workflow

Pros

• Enables large language models to access CyberChef’s broad recipe library without manual copy-paste
• Works with any MCP-compatible client for easy integration into agentic pipelines
• Written in Python, lowering the barrier for contributions or custom extensions

Cons

• Requires a running CyberChef API instance, adding deployment and latency overhead
• Small community with only 39 stars, meaning limited support and documentation
• Feature set depends entirely on the upstream CyberChef API version and its availability

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.