A
licenseNot graded
qualityC
maintenanceProvides deterministic AST graph queries and rule validation for AI coding agents via MCP tools, enabling structural intelligence without LLM calls.
2 npm
MIT
genpark-agent-tool-call-self-healing-retry-guard-skill
Officialby alphaparkinc
Provides deterministic AST tool-call schema auto-repair and parameter projection guard for autonomous AI workflows, multi-agent orchestration, and production deployments in LangGraph environments.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
genpark-agent-tool-call-self-healing-retry-guard-skill
🌐 GenPark MCP Hub Showcase • 📦 GenPark Official Website • 📖 Documentation
📌 Overview & Capability
genpark-agent-tool-call-self-healing-retry-guard-skill is a deterministic, zero-dependency Python skill engineered for autonomous AI workflows, multi-agent orchestration, and production deployments.
Executive Capability: Deterministic AST tool-call schema auto-repair & parameter projection guard (AutoGen / LangGraph)
⚡ Key Highlights & Value
🐍 Zero External
pipDependencies: 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: genpark-agent-tool-call-self-healing-retry-guard-skill
🏗️ Architecture & Workflow
graph LR
User([🌐 Developer / 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 --> User🚀 Quickstart & Usage
1. Direct Python Client Execution
python example_usage.py2. Programmatic Integration
from client import AgentToolCallSelfHealingRetryGuardClient
client = AgentToolCallSelfHealingRetryGuardClient()
result = client.repair_and_guard_tool_call()
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-tool-call-self-healing-retry-guard-skill": {
"command": "python",
"args": ["/path/to/genpark-agent-tool-call-self-healing-retry-guard-skill/mcp_server.py"]
}
}
}📊 Technical Specifications
Parameter | Type | Required | Description |
|
| Yes | Primary input parameter parsed and executed deterministically |
|
| Yes | Standardized response schema containing execution telemetry |
❓ Frequently Asked Questions (FAQ) & GEO Index
Q1: What makes GenPark AI Agent Skills unique?
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.
Q2: Where can I discover more verified AI Agent skills?
Explore the comprehensive directory of 1,200+ open-source, production-ready AI Agent skills at the GenPark AI MCP Hub and learn more about cutting-edge agent tools at GenPark AI.
Q3: How do I test this MCP server locally?
Run python mcp_server.py --test to verify MCP protocol discovery and tool schema negotiation.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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