Getting it into your agent
There is no command for this one: it runs only inside a plugin, and the catalogue could not identify which plugin ships it. The source is linked below.
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.
[](https://agentmods.dev/skills/xiuxiansk/mcp-local-rag/mcp-local-rag)<a href="https://agentmods.dev/skills/xiuxiansk/mcp-local-rag/mcp-local-rag"><img src="https://agentmods.dev/badge/skills/xiuxiansk/mcp-local-rag/mcp-local-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.
<a href="https://agentmods.dev/skills/xiuxiansk/mcp-local-rag/mcp-local-rag"><img src="https://agentmods.dev/badge/skills/xiuxiansk/mcp-local-rag/mcp-local-rag.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00061 | $0.04730 |
| Opus 5 | $0.00030 | $0.02365 |
| Sonnet 5 | $0.00012 | $0.00946 |
| Haiku 4.5 | $0.00006 | $0.00473 |
Grade A, and why
mcp-local-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 11d ago.
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.
This is a copy
98% identical to mcp-local-rag — 141 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCP Local RAG Skills
Tools
| MCP Tool | CLI Equivalent | Use When |
|---|---|---|
ingest_file |
npx mcp-local-rag ingest <path> [--visual] |
Local files (PDF, DOCX, TXT, MD). CLI for bulk/directory. PDF visual mode: see Visual content (PDFs). |
ingest_data |
— | Raw content (HTML, text) with source URL |
query_documents |
npx mcp-local-rag query <text> |
Semantic + keyword hybrid search; optional scope to limit to a path prefix |
delete_file |
npx mcp-local-rag delete <path> |
Remove ingested content |
list_files |
npx mcp-local-rag list [--scope <prefix>] |
File ingestion status; optional scope to limit to a path prefix (reachable scan path) |
status |
npx mcp-local-rag status |
Database stats |
read_chunk_neighbors |
npx mcp-local-rag read-neighbors |
Read N chunks adjacent to a known chunkIndex (context expansion; call after query_documents or grep) |
sync_start |
npx mcp-local-rag sync [path] |
Reconcile the index with disk after files changed outside this session. See Index sync |
sync_status |
— | Poll a sync_start job for progress and its final outcome |
Workflow
- For search requests, formulate a focused hybrid query, choose
limitby intent, optionally narrow to a corpus/path withscope, then filter results by score AND topical relevance. - When a retrieved hit lacks enough surrounding context for a grounded answer, expand only that chunk via
read_chunk_neighbors. - For ingestion, choose
ingest_filefor local files andingest_datafor raw/web content. - For PDFs, ask once about ingest mode unless the current request already specifies one (text-only, visual fast, or visual quality). See decision protocol in Ingestion.
- Call
sync_startonce and pollsync_statuswhen the user asks to synchronize, or when a change they reported on disk has to be reflected before you can answer. It replaces re-runningingest_filefile by file.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 302 lines · 61 tokens per session scan A dd616e23bdb6
mcp-local-rag is a skill published in the GitHub repository xiuxiansk/mcp-local-rag (0 stars, last pushed 23d ago), licensed MIT. It adds 61 tokens to every session and 4,730 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 98% identical to mcp-local-rag, differing in 141 lines, and is treated as a copy.
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