Skip to main content
Glama
Sign In
genpark-raft-leader-election-consensus-kernel-skill

genpark-raft-leader-election-consensus-kernel-skill

by alphaparkinc
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

genpark-raft-leader-election-consensus-kernel-skill

Python 3.9+ License MIT MCP Compatible GenPark AI Zero Dependencies

⚡ 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.

Related MCP server: genpark-raft-leader-election-consensus-kernel-skill

🏗️ Architectural Topology & State Machine

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

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:

{
  "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:

pip install git+https://github.com/alphaparkinc/genpark-raft-leader-election-consensus-kernel-skill.git

This server cannot be deployed

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Resources

Related MCP Connectors

Related MCP Servers

  • genpark-crdt-lww-element-set

    Alpha-Park
    A
    license
    Not graded
    quality
    B
    maintenance
    Enables agents to synchronize, merge, and reconcile distributed state across nodes using conflict-free last-write-wins element sets with Lamport/vector-clock causality, token-bucket gossip dissemination, and quorum-based commit coordination. It runs entirely on the Python standard library and exposes these primitives to Claude Desktop, Cursor, and Windsurf over the MCP JSON-RPC stdio protocol.
    7
    MIT

  • genpark-raft-leader-election

    Alpha-Park
    A
    license
    Not graded
    quality
    Not graded
    maintenance
    Enables MCP clients to run distributed Raft leader election, quorum voting, vector-clock causality tracking, LWW CRDT reconciliation, epidemic gossip, and two-phase commit coordination using only Python standard library. It supports local benchmarking and integration with Claude Desktop, Cursor, and Windsurf via JSON-RPC stdio.
    7
    MIT

  • genpark-vector-clock-causal

    Alpha-Park
    A
    license
    Not graded
    quality
    Not graded
    maintenance
    Enables agents to stamp events with vector clocks, resolve state via LWW CRDT reconciliation, and coordinate distributed swarms through token-bucket gossip, Raft leader/quorum voting, and two-phase commit. It runs over MCP with zero external dependencies, delivering deterministic happens-before causal ordering and convergence across agent networks.
    7
    MIT
  • genpark-multi-agent-token-bucket-gossip-protocol-skill

    genpark-multi-agent-tokenofficial

    alphaparkinc
    A
    license
    Not graded
    quality
    B
    maintenance
    Enables MCP clients to run bounded epidemic dissemination, causal ordering, conflict-free state merging, and quorum-based transaction coordination across autonomous agent swarms.
    7
    MIT