# Crypto

> Use this tool when you need to perform encryption, decryption, hashing, or digital signature operations in AI applications. It solves problems related to secure data handling by providing a standardized interface to cryptographic operations. With inputs such as plaintext, keys, and data, and outputs including ciphertext, hashes, and signatures, Crypto enables AI assistants to handle sensitive information securely.

Canonical page: https://skillsregistry.net/skills/kiss-kedaya-crypto  
JSON: https://api.skillsregistry.net/v1/skills/kiss-kedaya-crypto

## Description

Crypto MCP provides a bridge between language models and cryptographic operations using the PyCryptodome library. This implementation enables AI assistants to perform various encryption, decryption, hashing, and digital signature operations through a standardized interface. Built with Python and containerized with Docker, it offers a lightweight solution for secure data handling in AI applications where cryptographic capabilities are needed.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/kiss-kedaya-crypto)
- **Repository:** <https://github.com/kiss-kedaya/crypto_mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "kiss-kedaya-crypto"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kiss-kedaya-crypto` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kiss-kedaya-crypto/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt