genpark-raft-leader-election-consensus-kernel-skill
by alphaparkinc
README.md
# genpark-raft-leader-election-consensus-kernel-skill
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[](https://www.python.org/)
[](LICENSE)
[](https://genpark.ai/mcp)
[](https://genpark.ai)
[-brightgreen.svg?style=for-the-badge)](requirements.txt)
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<b>Production-Grade Distributed Swarm & Consensus Agent Skill</b> • <b>100% Standard Library Python</b> • <b>Native Model Context Protocol (MCP)</b>
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---
## ⚡ Overview & Architectural Significance
`genpark-raft-leader-election-consensus-kernel-skill` provides mathematically proven distributed systems, consensus coordination, and conflict-free replication primitives engineered strictly using Python 3.9+ standard library.
### 🌟 Key Architectural Capabilities
- **Zero External Dependencies**: Operates exclusively via pure Python (`time`, `math`, `json`, `uuid`). Zero socket/grpc compilation overhead, zero external dependencies.
- **Enterprise Distributed Invariants**: Implements formal LWW CRDT state reconciliation, Raft leader election terms & quorum validation, Vector Clock happens-before causal graphs, token-bucket gossip dissemination, and ACID 2-phase commit atomic coordination.
- **Native Anthropic MCP Protocol**: Compliant with standard JSON-RPC 2.0 stdio MCP specifications for Claude Desktop, Cursor, and Windsurf.
---
## 🏗️ Architectural Topology & State Machine
```mermaid
flowchart TD
ClientAgent["Client Agent Swarm Node"] --> VectorClock["Vector Clock Causal Stamping"]
VectorClock --> GossipNode["Token-Bucket Epidemic Gossip"]
GossipNode --> CRDTMerge["LWW CRDT Element State Reconciliation"]
CRDTMerge --> ConsensusCoordinator["Raft Leader / 2PC Transaction Coordinator"]
ConsensusCoordinator --> QuorumValidation["Quorum Voting & Commit Log Commit"]
QuorumValidation --> SwarmConvergence["Deterministic Swarm Convergence"]
```
---
## 🚀 Quickstart & Standalone Execution
### Local Python Client Usage
```python
from client import RaftLeaderElectionKernel
# Initialize engine
engine = RaftLeaderElectionKernel()
# Execute self-testing benchmark suite
result = engine.benchmark_election()
print("Execution Result:", result)
```
---
## 🔌 One-Click MCP Integration (Claude Desktop / Cursor)
Add to your `claude_desktop_config.json` or `cursor.json`:
```json
{
"mcpServers": {
"genpark-raft-leader-election-consensus-kernel-skill": {
"command": "python",
"args": ["-u", "/path/to/genpark-raft-leader-election-consensus-kernel-skill/mcp_server.py"]
}
}
}
```
---
## 📦 Smithery.ai & PyPI Deployment
This skill contains pre-configured `smithery.yaml` and `pyproject.toml` manifests. Install directly via pip:
```bash
pip install git+https://github.com/alphaparkinc/genpark-raft-leader-election-consensus-kernel-skill.git
```
---
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<sub>Maintained with ❤️ by <b><a href="https://genpark.ai">GenPark AI Engineering</a></b> • Powering Autonomous Distributed Swarms 🌍</sub>
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