3 #evaluation MCP Servers & Clients
Every MCP server and client below is tagged #evaluation — install one to give Claude, Cursor, VS Code, or any other MCP-compatible client access to evaluation tools.
All
Pqs Prompt Quality Score
OnChainAIIntel
The world's first named AI prompt quality score. Score any LLM prompt before it hits any model — returns grade (A-F), score out of 40, percentile, and dimension breakdown across 8 quality dimensions.
Okareo
okareo-ai
Simulate and evaluate voice & text agents from your editor. Generate synthetic-user "Drivers" from your codebase, run multi-turn simulations against your agents, and pull back transcripts, traces, and scores without leaving your AI assistant.
Iris
iris-eval
The first MCP-native eval and observability tool for AI agents. Any MCP-compatible agent discovers and uses Iris automatically — no SDK, no code changes. Log traces with hierarchical span trees, evaluate output quality with 12 built-in rules (PII detection, prompt injection, cost
Frequently asked questions
What is a #evaluation MCP server?
- An MCP server tagged #evaluation implements the Model Context Protocol so AI assistants like Claude, Cursor, and VS Code can access evaluation-related tools, data, or APIs.
How many #evaluation MCP servers and clients are there?
- mcp.so currently lists 3 MCP servers and clients tagged #evaluation.
How do I install a #evaluation MCP server?
- Open any server below and copy its install snippet into Claude Desktop, Cursor, VS Code, or another MCP client's configuration — remote servers need no separate download.