genpark-schnorr-zero-knowledge-prover-skill

⚡ Overview & Architectural Significance

genpark-schnorr-zero-knowledge-prover-skill delivers zero-dependency, mathematically sound cryptographic attestation, zero-knowledge verification, and cybersecurity primitives engineered strictly using Python 3.9+ standard library.

🌟 Key Architectural Capabilities

• Zero External Dependencies: Operates exclusively via pure Python (hashlib, hmac, secrets, time, json). Zero OpenSSL or C binding failures.

• Enterprise Security Invariants: Implements formal SHA-256 Merkle root verification, RFC 7519 JWT HMAC-SHA256 signature parsing, 3-pass Schnorr zero-knowledge identification, constant-time equality validation, and sliding-window nonce replay protection.

• Native Anthropic MCP Protocol: Compliant with standard JSON-RPC 2.0 stdio MCP specifications for Claude Desktop, Cursor, and Windsurf.

🏗️ Architectural Topology & State Machine

flowchart TD
    InboundPayload["Inbound Agent Request & Auth Payload"] --> ReplayGuard["Sliding-Window Nonce Replay Guard"]
    ReplayGuard --> ConstantTimeCheck["Constant-Time Secret Digest Comparison"]
    ConstantTimeCheck --> TokenValidator["JWT HMAC-SHA256 Claims Validator"]
    TokenValidator --> MerkleProof["Merkle Tree State Inclusion Proof"]
    MerkleProof --> ZKPVerification["Schnorr Zero-Knowledge Proof Verifier"]
    ZKPVerification --> SecureStateAttestation["Cryptographically Attested Agent Execution"]

🚀 Quickstart & Standalone Execution

Local Python Client Usage

from client import SchnorrZeroKnowledgeProver

# Initialize engine
engine = SchnorrZeroKnowledgeProver()

# Execute self-testing benchmark suite
result = engine.benchmark_schnorr_zkp()
print("Execution Result:", result)

🔌 One-Click MCP Integration (Claude Desktop / Cursor)

Add to your claude_desktop_config.json or cursor.json:

{
  "mcpServers": {
    "genpark-schnorr-zero-knowledge-prover-skill": {
      "command": "python",
      "args": ["-u", "/path/to/genpark-schnorr-zero-knowledge-prover-skill/mcp_server.py"]
    }
  }
}

📦 Smithery.ai & PyPI Deployment

This skill contains pre-configured smithery.yaml and pyproject.toml manifests. Install directly via pip:

pip install git+https://github.com/alphaparkinc/genpark-schnorr-zero-knowledge-prover-skill.git