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genpark-agent-self-consistency-consensus-scorer-skill

genpark-agent-self-consistency-consensus-scorer-skill

by Alpha-Park

genpark-agent-self-consistency-consensus-scorer-skill

Python 3.9+ License MIT MCP Compatible GenPark AI Zero Dependencies

🌐 GenPark MCP Hub β€’ πŸ“¦ GenPark Official β€’ πŸ“– Documentation


πŸ“Œ Overview & Capability

genpark-agent-self-consistency-consensus-scorer-skill is a deterministic, high-performance, zero-dependency Python tool and native Model Context Protocol (MCP) server designed for autonomous AI agents, multi-agent frameworks (LangGraph, CrewAI, AutoGen, OpenAI Swarm), and developer environments (Cursor, Windsurf, Claude Desktop).

Executive Capability: Multi-path chain-of-thought self-consistency consensus scorer and majority voter aggregating divergent LLM reasoning trajectories into high-confidence deterministic outputs.

⚑ Key Highlights

  • 🐍 Zero External pip Dependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.

  • πŸ”Œ Native Model Context Protocol (MCP): Plugs directly into any MCP-compliant client via JSON-RPC 2.0 stdio.

  • ⚑ Sub-Millisecond Execution: Slashes token burn and latency by resolving routine agent tasks deterministically without frontier LLM round-trips.

  • πŸ›‘οΈ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.


Related MCP server: genpark-deep-research-consensus-engine-skill

πŸ—οΈ Architecture

graph LR
    Agent([πŸ€– Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚑ genpark-agent-self-consistency-consensus-scorer-skill Server]
    Server --> Core[🧠 Deterministic Processing Core]
    Core --> Out[πŸ“Š Actionable Result & Telemetry]
    Out --> Agent

πŸš€ Quickstart & Usage

1. Direct Python Client Execution

python example_usage.py

2. Programmatic Integration

from client import AgentSelfConsistencyConsensusScorer

client = AgentSelfConsistencyConsensusScorer()
result = client.run_consensus_benchmark()
print(result)

πŸ”Œ Model Context Protocol (MCP) Setup

Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:

claude_desktop_config.json

{
  "mcpServers": {
    "genpark-agent-self-consistency-consensus-scorer-skill": {
      "command": "python",
      "args": ["/path/to/genpark-agent-self-consistency-consensus-scorer-skill/mcp_server.py"]
    }
  }
}

Direct MCP Testing

python mcp_server.py --test

πŸ“Š Technical Specifications

Parameter

Type

Required

Description

payload

string / dict

Yes

Primary context, code, schema, or content input

options

dict

No

Execution flags, compression ratios, or risk bounds


Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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