genpark-agent-rate-limit-token-bucket-regulator-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-agent-rate-limit-token-bucket-regulator-skillthrottle my agent's OpenAI calls to 80,000 TPM and 500 RPM"
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-agent-rate-limit-token-bucket-regulator-skill
🌐 GenPark MCP Hub • 📦 GenPark Official • 📖 Documentation
📌 Overview & Capability
genpark-agent-rate-limit-token-bucket-regulator-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-provider token-bucket and sliding-window rate limiter preventing TPM/RPM throttling across LLM APIs with predictive token consumption budgeting.
⚡ Key Highlights
🐍 Zero External
pipDependencies: Implemented entirely with pure Python standard library for instant zero-overhead execution.🔌 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.
🛡️ Production-Hardened: Comprehensive error handling, boundary validation, and telemetry.
Related MCP server: genpark-api-rate-limit-token-bucket-throttle-skill
🏗️ Architecture
graph LR
Agent([🤖 Autonomous Agent / IDE]) -->|MCP Protocol / JSON-RPC| Server[⚡ genpark-agent-rate-limit-token-bucket-regulator-skill Server]
Server --> Core[🧠 Deterministic Processing Core]
Core --> Out[📊 Actionable Result & Telemetry]
Out --> Agent🚀 Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Programmatic Integration
from client import AgentRateLimitRegulator
client = AgentRateLimitRegulator()
result = client.run_rate_limiter_benchmark()
print(result)🔌 Model Context Protocol (MCP) Setup
Connect this skill to Claude Desktop, Cursor, or any MCP-compliant client:
claude_desktop_config.json
{
"mcpServers": {
"genpark-agent-rate-limit-token-bucket-regulator-skill": {
"command": "python",
"args": ["/path/to/genpark-agent-rate-limit-token-bucket-regulator-skill/mcp_server.py"]
}
}
}Direct MCP Testing
python mcp_server.py --test📊 Technical Specifications
Parameter | Type | Required | Description |
|
| Yes | Primary context, code, schema, or content input |
|
| No | Execution flags, compression ratios, or risk bounds |
This server cannot be deployed
Maintenance
Related MCP Connectors
Token guard and rate limiter preventing runaway API cost spikes for OpenAI and Anthropic.
Agent Cost Allocator MCP — multi-tenant LLM cost attribution for chargeback billing. Companion to
AgentGuard — 20-tool AI safety MCP: policy preflight, risk scoring, audit logging, rate limits.
Hosted MCP server for LLM cost estimation, model comparison, and budget-aware routing.
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceTransparent rate-limiting MCP proxy that prevents HTTP 429 errors by throttling API calls and tokens. Includes tools to check usage and dynamically adjust rate limits.109 npm2MIT
- FlicenseNot gradedqualityBmaintenanceEnables high-throughput API rate limiting with deterministic token bucket throttling and burst quota management for AI agents.8-
- FlicenseNot gradedqualityBmaintenanceEnables autonomous agents to apply adaptive token bucket concurrency limits and backoff scheduling to avoid HTTP 429 errors. It provides deterministic rate-limiting permits and structured telemetry through MCP-compatible clients.8-
- FlicenseNot gradedqualityBmaintenanceEnables adaptive token bucket rate limiting and backoff scheduling to prevent HTTP 429 errors for autonomous agents and API clients. Provides a deterministic zero-dependency MCP/CLI engine for acquiring token permits and returning structured telemetry.7-