Chepy MCP Service (CyberChef like Python library)
About
This project exposes the powerful Chepy data transformation library as an MCP server. It allows you to access Chepy's tools (like encoding, decoding, and data manipulation) via a single flexible API: the bake pipeline tool, inspired by CyberChef.
Details
- Author
- nebucaz
- Downloads
- 277
- Categories
- Developer Tools
Jump to
- Pipeline tool (bake) chains multiple Chepy operations in one request
- Uses Chepy’s own recipe JSON format, compatible with Chepy’s CLI
- Resource endpoint lists all operations with parameters and descriptions
- Output indicates whether result is text or binary ("type": "text" or "type": "binary")
- Includes a unittest-based test suite for validation
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Chepy MCP Service (CyberChef like Python library)Command (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install uv, clone the repository, run uv sync to install dependencies, then start the server with uv run src/server.py. Use the bake tool by sending a recipe in Chepy JSON format containing input and a recipe list of operations with their arguments. Discover all available operations by fetching resource://chepy_operations.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"chepy mcp service (cyberchef like python library)": {
"chepy-mcp": {
"command": "/Users/username/.local/bin/uv",
"args": [
"--directory",
"/Users/username/chepy-mcp",
"run",
"src/server.py"
]
}
}
}
}McpServers
{
"chepy-mcp": {
"command": "/Users/username/.local/bin/uv",
"args": [
"--directory",
"/Users/username/chepy-mcp",
"run",
"src/server.py"
]
}
}Chepy MCP Service
This project exposes the powerful Chepy data transformation library as an MCP (Model Context Protocol) server. It allows you to access Chepy's tools (like encoding, decoding, and data manipulation) via a single flexible API: the bake pipeline tool, inspired by CyberChef.
Features
- Single pipeline tool (bake): Chain one or more Chepy operations, each with parameters, in a single request
- Chepy recipe JSON format: Pipelines are described using Chepy's own recipe serialization, making them compatible with Chepy's import/export and CLI tools
- Resource endpoint: Discover all available Chepy operations and their signatures
- Unittest-based test suite for robust validation
Installation
1. Install uv if it is not installed yet. $ curl -LsSf https://astral.sh/uv/install.sh | sh
2. Clone the repository:
git clone https://github.com/nebucaz/chepy-mcp.git
cd chepy-mcp
3. Install dependencies:
uv sync
Run
Run the server with:
$ uv run src/server.py
Usage
The Chepy Recipe JSON Format
The bake tool expects a pipeline in the Chepy recipe JSON format:
{
"input": "hello world",
"recipe": [
{"function": "to_base64", "args": {}},
{"function": "from_base64", "args": {}}
]
}
- Each step in the recipe list is an object with a function (the Chepy operation name) and args (a dictionary of arguments for that function).
- This format is fully compatible with Chepy's own recipe import/export and CLI tools.
The response will indicate if the output is text or binary:
{
"type": "text",
"data": "hello world"
}
Discover Available Operations
Fetch the resource endpoint to get all available Chepy operations, their parameter signatures, and descriptions:
- Resource URI: resource://chepy_operations
Example response:
{
"to_base64": {
"signature": "(alphabet: str = 'standard')",
"description": "Encode the input string to base64"
},
"from_base64": {
"signature": "(alphabet: str = 'standard', remove_non_alpha: bool = True)",
"description": "Decode base64 encoded string"
}
}
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