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Ragmetric Mcp

mukundakatta/mcp-stack

Provides five information retrieval scoring tools for evaluating RAG system quality: recall@k and hit@k measure whether relevant documents appear in your top results, MRR scores the rank of the first correct match, NDCG@k weights graded relevance scores by position, and evaluate_batch runs all metrics on multiple queries at once. Complements the author's promptbudget, citecite, and ragdrift servers from the same mcp-stack collection. Install it when you need Claude to help you benchmark retriever performance against ground truth relevance judgments, either interactively or as part of a larger RAG development workflow. The logic is implemented in plain JavaScript so you can run it via npx without pulling in the Rust ragmetric crate.

tools: 5
transport: STDIO
last updated: May 10, 2026

Tools

5 tools

Public tool metadata for what this MCP can expose to an agent.

recall_at_kLLM helps score retrieval quality

LLM helps score retrieval quality

No parameter schema in public metadata yet.

hit_at_k

No parameter schema in public metadata yet.

mrr

No parameter schema in public metadata yet.

ndcg_at_k

No parameter schema in public metadata yet.

evaluate_batch

No parameter schema in public metadata yet.

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Readme

mcp-stack

Fourteen small MCP servers for everyday LLM / RAG / agent work. Each ships independently on npm, listed in the official MCP Registry, and is callable from Claude Desktop, Cursor, Cline, Windsurf, Zed, and any other MCP-compatible client.

RAG / agent helpers

Package	Tools	When to install
`@mukundakatta/promptbudget-mcp`	`truncate_to_token_budget`	LLM needs to fit text into a context window mid-task
`@mukundakatta/citecite-mcp`	`inject_citations`, `parse_citations`, `strip_citations`	Round-trip `[1] [2]` markers in RAG outputs
`@mukundakatta/ragmetric-mcp`	`recall_at_k`, `hit_at_k`, `mrr`, `ndcg_at_k`, `evaluate_batch`	LLM helps score retrieval quality
`@mukundakatta/ragdrift-mcp`	`interpret_drift_score`, `recommend_thresholds`, `explain_drift_dimensions`	LLM diagnoses RAG drift alerts

Reliable transforms LLMs reach for tools instead of imagining

View the full README on GitHub

Details

Repository: github.com/mukundakatta/mcp-stack
Category: AI & LLM Tools
Package: @mukundakatta/ragmetric-mcp
Transport: STDIO
Registry: MCP registry, active

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