Provides capabilities for Cloudflare edge AI low-latency geo-distributed request routing governance, enabling management of edge request routing policies and telemetry.
Click on "Install 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-edge-geo-distributed-request-routing-governor-skill Route this user request to the lowest-latency edge region."
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.
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genpark-edge-geo-distributed-request-routing-governor-skill is a deterministic, zero-dependency Python skill engineered for autonomous AI agents, multi-agent frameworks (Claude Desktop, Cursor, AutoGPT, CrewAI), and enterprise pipelines.
Executive Capability: Edge AI low-latency geo-distributed request routing governor (Cloudflare)
🐍 Zero External pip Dependencies: Runs instantly on standard Python 3.9+ with zero environment bloat.
🔌 Native Model Context Protocol (MCP): Seamlessly plugs into Cursor IDE, Claude Desktop, and Windsurf.
🎯 Deterministic & Reliable: 100% predictable input/output contracts with full JSON Schema validation.
🚀 Low Latency: Sub-millisecond execution overhead tailored for high-concurrency production agents.
Related MCP server: ToolRoute
graph LR
User([🌐 User / AI Agent]) -->|JSON-RPC Request| MCP[⚡ MCP Server / CLI]
MCP --> Client[🛠️ Skill Client Core Engine]
Client --> Engine[🧠 Algorithmic Execution Kernel]
Engine --> Output[📊 Structured Output Dossier & Telemetry]
Output --> Userpython example_usage.pyfrom client import EdgeGeoDistributedRequestRoutingGovernorClient
client = EdgeGeoDistributedRequestRoutingGovernorClient()
result = client.route_agent_request()
print(result)Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json{
"mcpServers": {
"genpark-edge-geo-distributed-request-routing-governor-skill": {
"command": "python",
"args": ["/path/to/genpark-edge-geo-distributed-request-routing-governor-skill/mcp_server.py"]
}
}
}Parameter | Type | Required | Description |
|
| Yes | Primary input parameter parsed and executed deterministically |
|
| Yes | Standardized response schema containing execution telemetry |
GenPark AI Agent Skills are engineered with zero external dependencies using pure Python standard library code. This ensures maximum portability, instantaneous cold starts, and zero package version conflicts across diverse agent runtime environments.
Explore the comprehensive directory of 1,160+ open-source, production-ready AI Agent skills at the GenPark AI MCP Hub and learn more about agentic shopping and commerce at GenPark AI.
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
This server cannot be installed
AI routing, memory, guardrails, and governance. Routes across Claude, GPT, Gemini.
Enterprise AI Control Plane: governance, guardrails, spend tracking, compliance & smart routing.
Pre-execution governance for AI agents. Deterministic PASS/FAIL/REVIEW verdicts, replayable proof.
Independent, trusted, and verified advisories and routing for agentic workflows on the web.
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