A command for inspecting and changing the settings of a retrieval-augmented generation (RAG) answer pipeline. RAG retrieves relevant passages before a language model writes an answer.

Use it to show configuration, change the passage count, choose an embedding model or reranker, set up the tool, or check what is installed.

It avoids manually editing configuration when you need to check the setup, change how many passages are used, or select embedding and reranking options.

rag — Command for Claude Code by MasihMoafi/rag-mcp

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo

git clone --depth 1 https://github.com/MasihMoafi/rag-mcp

Made for: Claude Code.

Or install rag, the plugin that ships this one along with the rest of its 1 skill, 1 command, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/commands/masihmoafi/rag-mcp/rag/github.svg)](https://agentmods.dev/commands/masihmoafi/rag-mcp/rag)

Your own site

<a href="https://agentmods.dev/commands/masihmoafi/rag-mcp/rag"><img src="https://agentmods.dev/badge/commands/masihmoafi/rag-mcp/rag/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/commands/masihmoafi/rag-mcp/rag"><img src="https://agentmods.dev/badge/commands/masihmoafi/rag-mcp/rag.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 21 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 250 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00021	$0.00250
Opus 5.5	$0.00008	$0.00100
Sonnet 5.5	$0.00004	$0.00050
Haiku 4.5	$0.00002	$0.00025

Measured yesterday against content hash a2f1b564ccb7, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

rag scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

claude-plugin/commands/rag.md · 15 lines

What it actually says

The user wants to change or inspect their RAG answer pipeline: $ARGUMENTS

Use the rag command line tool through the shell (if rag is not on PATH, use uvx ragmcp with the same arguments). Map the request to exactly one of these and run it:

rag config show
rag config top <N> (also for "top5", "top 5", "use 5 passages for the answer")
rag config reranker off|auto|fastembed|openrouter|<model>
rag config embedding <model> [--provider fastembed|ollama|openai_compatible|sentencetransformer]
rag setup --auto (start over with what this machine already has)
rag doctor (what is installed and running) Never ask for or paste API keys in this chat; for keys, tell the user to run rag setup in a terminal. Finish by running rag config show and report its lines to the user, nothing more.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

yesterday First seen · 15 lines · 21 tokens per session scan A a2f1b564ccb7

Subscribe to this mod's changes

rag is a command published in the GitHub repository MasihMoafi/rag-mcp (7 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 250 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-16.

Data and AI RAG and vectors

rag

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

What it actually says

What this file has done since we first saw it

Other commands, from other repositories

querying

agent

ingest

inference.embed

vector.batch_exists

proofrag