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enigma-python-mcp

Enigma Python MCP Server

An MCP (Model Context Protocol) server that brings the capabilities of the enigmapython library to LLMs, allowing them to encrypt and decrypt messages using historically accurate Enigma machine emulators.

Claude Desktop Integration

PyPI version Python Versions Downloads License: MIT Publish Status

This MCP Server is listed on Glama.ai with this score

enigma-python-mcp MCP server

Features

  • Exposes all known Enigma machine models: Enigma M3, Enigma M4, Enigma I, Enigma K, Enigma Z, Enigma D, Enigma T, and more.

  • Dynamic Configuration: LLMs can specify rotors, initial positions, ring settings, reflectors, and plugboard pairs for the encryption.

  • Local and Network Mode: Supports both stdio transport for local MCP integrations (like Claude Desktop) and sse transport to expose the tools over a network.

  • Dockerized: Easy portability and execution across platforms.

Related MCP server: MCP Server Example

Exposed Tools

encrypt_message

Encrypt or decrypt a message using a configured Enigma machine.

Arguments:

  • machine_model (str): Model name. Supported: 'M3', 'M4', 'I', 'I_Norway', 'I_Sondermaschine', 'K', 'K_Swiss', 'D', 'Z', 'B_A133', 'T'.

  • message (str): The plaintext or ciphertext to process.

  • rotors (list[object]): List of RotorConfig objects. Each object specifies rotor_type (str), ring_setting (int, default=0), and initial_position (int | str, default=0). IMPORTANT: The list MUST be ordered exactly as: [Fastest/Rightmost, Middle, Slowest/Leftmost, Greek (if M4)].

  • reflector (object): A ReflectorConfig object specifying reflector_type (str), and optionally ring_setting (int) and initial_position (int | str) for rotating reflectors.

  • plugboard_pairs (dict, optional): Dictionary mapping plugboard connections (e.g., {"A": "B", "C": "D"}).

Running the Server

Using Python

Requires Python 3.11+.

  1. Install the package from PyPI:

    pip install enigmapython-mcp

    (Alternatively, you can just run uvx enigmapython-mcp if you have uv installed!)

  2. Run via stdio (for local MCP client):

    enigmapython-mcp --transport stdio
  3. Run via SSE (exposing over network):

    enigmapython-mcp --transport sse --host 0.0.0.0 --port 8000

Using Docker

  1. Build the container:

    docker build -t enigmapython-mcp .
  2. Run via stdio (default):

    docker run -i enigmapython-mcp
  3. Run via SSE:

    docker run -p 8000:8000 enigmapython-mcp --transport sse --host 0.0.0.0 --port 8000

Client Configuration (Claude Desktop)

We provide two distinct mcpb bundles for 1-click installation on Claude Desktop. Simply download your preferred bundle from the GitHub Releases page and drag-and-drop it into Claude Desktop's Extensions menu:

  1. enigmapython-mcp-docker.mcpb: Extremely lightweight, relies on your local Docker daemon to run the server in an isolated container. (Recommended)

  2. enigmapython-mcp-python.mcpb: Contains the full Python source. Claude Desktop will natively build a virtual environment and run the server without needing Docker.

If you prefer manual configuration via claude_desktop_config.json, use the settings below:

{
  "mcpServers": {
    "enigma": {
      "command": "uvx",
      "args": ["enigmapython-mcp", "--transport", "stdio"]
    }
  }
}

Using Docker

(Note: Make sure you have built the Docker image first: docker build -t enigmapython-mcp .)

{
  "mcpServers": {
    "enigma": {
      "command": "docker",
      "args": ["run", "-i", "--rm", "enigmapython-mcp"]
    }
  }
}

Client Configuration (OpenCode)

To use this server with OpenCode, add the following to your ~/.config/opencode/opencode.json (global) or opencode.json (project-level) under the mcp section:

{
  "mcp": {
    "enigma": {
      "type": "local",
      "command": [
        "uvx",
        "enigmapython-mcp",
        "--transport",
        "stdio"
      ],
      "enabled": true
    }
  }
}

Using Docker

(Note: Make sure you have built the Docker image first: docker build -t enigmapython-mcp .)

{
  "mcp": {
    "enigma": {
      "type": "local",
      "command": [
        "docker",
        "run",
        "-i",
        "--rm",
        "enigmapython-mcp"
      ],
      "enabled": true
    }
  }
}

Example Prompts

Once the server is configured, you can test it by sending the following prompts to your LLM:

Example 1: Basic Encryption (Enigma M3)

"I need to encrypt the message 'TOPSECRET' using an Enigma M3. The rotors, ordered from fastest to slowest, are III, II, and I. All starting at position 0 with ring settings at 0. Use reflector 'UKWB' and no plugboard. What is the ciphertext?"

Example 2: Historical Decryption (Enigma I)

"Decrypt this 1930 Enigma I message. The ciphertext is 'GCDSEAHUGWTQGRK'. The machine settings, strictly ordered from Fastest to Slowest, are: Rotors III, I, and II. Their respective ring settings are 21, 12, and 23. Their initial positions are 11, 1, and 0. The reflector is 'UKWA'. The plugboard swaps are: A/M, F/I, N/V, P/S, T/U, W/Z."

Example 3: Complex M4 Configuration

"Use the Enigma M4 to encrypt the message 'DIVE DIVE DIVE'. The machine uses the 'UKWBThin' reflector. The rotors, explicitly ordered as [Fastest, Middle, Slowest, Greek], are: VIII (pos 2), III (pos 6), IV (pos 12), and Gamma (pos 21). All ring settings are 0. Please process this."

Testing

A comprehensive test suite is included in tests/test_server.py. It tests the encryption and decryption reversibility for all 10 supported Enigma models.

To run the tests:

# Activate your virtual environment first
source .venv/bin/activate

pip install pytest
export PYTHONPATH=$PYTHONPATH:$(pwd)/src/enigmapython_mcp && pytest tests/* 

Testing the SSE Server interactively

Because the Model Context Protocol requires a stateful initialization handshake before any tools can be called, manually testing the SSE endpoint with curl is quite complex.

The easiest and officially recommended way to test the server is using the MCP Inspector:

  1. Ensure your server is running in SSE mode:

    uv run enigmapython-mcp --transport sse --host 0.0.0.0 --port 8000
  2. In a second terminal, launch the Inspector:

    npx @modelcontextprotocol/inspector
  3. A web interface will open in your browser (usually at http://localhost:5173).

  4. Change the Transport Type to SSE.

  5. Enter http://localhost:8000/sse as the URL and click Connect.

  6. You can now visually configure and execute the encrypt_message tool!

Available Tools

1 tool
encrypt_messageA
Encrypt or decrypt a message using a specified Enigma machine configuration.

Args:
    machine_model: Exact machine model name. MUST be one of: 'M3', 'M4', 'I', 'I_Norway', 'I_Sondermaschine', 'K', 'K_Swiss', 'D', 'Z', 'B_A133', 'T'. Do not add 'Enigma' prefix.
        Supported models and their explicitly required reflectors:
        - 'M3', 'I': UKWA, UKWB, UKWC
        - 'M4': UKWBThin, UKWCThin
        - 'I_Norway': UKW_EnigmaINorway
        - 'I_Sondermaschine': UKW_EnigmaISonder
        - 'K', 'K_Swiss', 'D': UKW_EnigmaCommercial
        - 'Z': UKW_EnigmaZ
        - 'B_A133': UKW_EnigmaB_A133
        - 'T': UKW_EnigmaT
    message: The plaintext or ciphertext to process.
        - For Enigma Z: MUST contain ONLY digits (1234567890).
        - For Enigma B_A133: MUST contain ONLY Swedish letters (abcdefghijklmnopqrstuvxyzåäö). Note: 'w' is strictly forbidden.
        - For all other machines: MUST contain ONLY standard letters (A-Z).
        - Spaces, punctuation, and special characters are strictly forbidden in all machines.
    rotors: List of RotorConfig objects. MUST be ordered exactly as: [Fastest/Rightmost, Middle, Slowest/Leftmost, Greek (if M4)].
    reflector: The ReflectorConfig object.
    plugboard_pairs: Optional dict for plugboard connections (e.g. {"A": "B", "C": "D"}). Ignored if the machine has no plugboard.
ParametersJSON Schema
NameRequiredDescriptionDefault
rotorsYes
messageYes
reflectorYes
machine_modelYes
plugboard_pairsNo

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It adds valuable behavioral context such as message character restrictions per machine model, rotor ordering, and plugboard being ignored when absent. However, it does not disclose return behavior, error handling, or side effects, leaving some transparency gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then structured as an 'Args' list. It is lengthy due to the complexity, but each line adds necessary value. A slightly more compressed format could be achieved without losing information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complex nested schema and no output schema, the description covers all input parameters thoroughly, including valid values and constraints. It does not explicitly state the return value, but that is implied by the encrypt/decrypt purpose. Overall, it is complete enough for a well-equipped agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% top-level description coverage, but the description provides exhaustive semantics for every parameter: allowed machine models, per-model message constraints, rotor ordering, reflector guidance, and plugboard behavior. This fully compensates for the missing schema documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with 'Encrypt or decrypt a message using a specified Enigma machine configuration,' which clearly states the verb and resource. However, there are no sibling tools to differentiate from, so it loses a point for not distinguishing alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus alternatives (though there are none), nor any prerequisites, exclusions, or context beyond the first sentence. The detailed parameter constraints are helpful but do not address usage scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

TDQS

A3.8/5.0
Disambiguation5/5

Only one tool exists, so there is no ambiguity between tools. The single tool's purpose is clear from its description.

Naming Consistency5/5

The single tool name 'encrypt_message' follows a clear verb_noun pattern, and there are no other tools to create inconsistency. The name is slightly misleading as it also performs decryption, but this does not affect consistency across tools.

Tool Count3/5

With only one tool, the server feels very thin for an Enigma machine library. However, the single tool is comprehensive, covering encryption and decryption for many machine models.

Completeness4/5

The tool covers both encryption and decryption, which are the core operations. It also supports a wide range of Enigma models. There could be additional tools for listing models or validating configurations, but these are minor gaps.

Maintenance

ActivitySlowing
ResponsivenessUnresponsive

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