genpark-schnorr-zero-knowledge-prover-skill
OfficialClick on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@genpark-schnorr-zero-knowledge-prover-skillprove I know my secret key without revealing it"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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.
Related MCP server: AccordTrace
🏗️ 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.gitThis server cannot be deployed
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