Kryve Agent Evaluation MCP
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., "@Kryve Agent Evaluation MCPGenerate a test plan for our customer support agent."
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.
Kryve Agent Evaluation MCP
Un serveur MCP local et open source pour concevoir des tests d’agents IA, noter une exécution et documenter les preuves avant d’accorder davantage d’autonomie.
Il expose trois outils en lecture seule :
generate_test_plan: construit des cas nominaux, ambigus et sensibles selon le niveau de risque ;score_agent_run: note le résultat, les preuves, le respect des validations et le coût des corrections ;evaluation_scorecard: renvoie les colonnes d’une scorecard réutilisable.
Installation
npm install
npm run buildPuis lance le serveur sur stdio :
npm startConfiguration d’un client MCP :
{
"mcpServers": {
"kryve-agent-eval": {
"command": "node",
"args": ["/chemin/vers/kryve-agent-eval-mcp/dist/src/index.js"]
}
}
}Related MCP server: llamator-mcp-server
Tester avec MCP Inspector
npx @modelcontextprotocol/inspector node dist/src/index.jsPhilosophie
Une démo réussie ne prouve pas qu’un agent est fiable. Le test doit mesurer un résultat attendu, conserver des preuves, détecter les actions hors permission et rendre visible le coût des corrections humaines.
Pour comprendre le protocole et choisir une infrastructure :
Le kit CSV complémentaire est disponible dans le dépôt Kryve Agent Evaluation Kit.
Limites
Le score est une grille opérationnelle simple, pas une certification. Adapte les cas, les seuils et les validations au risque réel de ton organisation.
Licence
MIT — Kryve Solutions.
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Maintenance
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