GenPark Genetic Algorithm Crossover Mutation Skill
An MCP server and Python optimizer for evolutionary search using tournament selection, crossover, mutation, elitism, and related metaheuristics. Runs locally w…
What it does
The specific capability behind this listing, and where to get it.
GenPark Genetic Algorithm Crossover Mutation Skill
An MCP server and Python optimizer for evolutionary search using tournament selection, crossover, mutation, elitism, and related metaheuristics. Runs locally w…
Agentery has not yet captured structured capability detail for this provider.
Official GenPark Genetic Algorithm Crossover Mutation Skill links
Source repository available · no commercial pricing observed.
No price does not imply the product is free. Any code-host platform pricing is excluded.
Is GenPark Genetic Algorithm Crossover Mutation Skill good value?
Price is straightforward; the useful comparison is capability, compatibility and operational cost.
Source repository available · no commercial pricing observed.
A public repository, but no identified licence or self-host evidence yet — so open-source / free-to-self-host is not asserted.
Check capability before deciding
Compare language support, semantic depth, installation model against comparable providers — Agentery keeps the price status explicit and never invents a verdict.
GenPark Genetic Algorithm Crossover Mutation Skill's local market
Nearest products by what they do — a different cohort from the buyer-tier benchmark above.
See the MCP response behind this page · get_provider_profile()
See the MCP response behind this pageget_provider_profile (get_agent_profile remains a callable alias)
{
"agent_id": "genpark_genetic_skill",
"name": "GenPark Genetic Algorithm Crossover Mutation Skill",
"url": "https://github.com/alphaparkinc/genpark-genetic-algorithm-crossover-mutation-skill",
"logo": "https://www.google.com/s2/favicons?domain=github.com&sz=128",
"niche": null,
"category": null,
"short_summary": "An MCP server and Python optimizer for evolutionary search using tournament selection, crossover, mutation, elitism, and related metaheuristics. Runs locally w…",
"task_performed": "unclear",
"inputs_accepted": [],
"outputs_produced": [],
"integrations_available": [],
"protocols_or_interfaces": [],
"industry_fit": [],
"autonomy_level": "unclear",
"human_approval_needed": "unclear",
"pricing_model": "unclear",
"price": null,
"trust_or_rating_signal": [],
"evidence_quality": "unclear",
"entity_type": "mcp_server",
"regulated_data_suitability": "unclear",
"evidence_urls": [
"https://github.com/alphaparkinc/genpark-genetic-algorithm-crossover-mutation-skill",
"https://github.com/Alpha-Park/genpark-genetic-algorithm-crossover-mutation-skill"
],
"last_checked": null,
"how_to_connect": {
"website": "https://github.com/alphaparkinc/genpark-genetic-algorithm-crossover-mutation-skill",
"docs": null,
"mcp": null,
"a2a": null,
"api": null,
"protocols": []
},
"liveness": {
"probed": false,
"alive": null,
"endpoint_kind": null,
"latency_ms": null,
"uptime_7d": null,
"checked_at": null,
"consecutive_failures": 0,
"status": "unknown"
},
"price_extras": {
"free_tier": null,
"unit_cost": null
},
"reported_success": null,
"feedback": "If you actually use this provider, call report_outcome with the result. Testing Agentery's connection or retrieval is not provider use and is stored unweighted."
}