General

papi-ask - Claude MCP Skill

Query papers using RAG (PaperQA2 or LEANN). Use when user needs synthesized answers from papers, asks "what does paper X say about Y", or needs cited responses.

SEO Guide: Enhance your AI agent with the papi-ask tool. This Model Context Protocol (MCP) server allows Claude Desktop and other LLMs to query papers using rag (paperqa2 or leann). use when user needs synthesized answers from papers, ask... Download and configure this skill to unlock new capabilities for your AI workflow.

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SKILL.md
# Query Papers via RAG

Use `papi ask` for questions requiring synthesis across papers or cited answers.

## Cost-Aware Retrieval

Before using RAG, consider cheaper alternatives:

1. **Exact match**: `papi search --rg "query"` — fast, no LLM
2. **Ranked search**: `papi search "query"` — BM25 ranking
3. **Direct read**: `papi show <paper> -l eq|tex|summary` — if you know the paper

Use `papi ask` only when:
- User explicitly requests RAG/synthesis
- Question spans multiple papers
- Search/show cannot answer

## Commands

```bash
# PaperQA2 (default) — full RAG with citations
papi ask "question"

# LEANN — faster semantic search + LLM
papi ask "question" --backend leann

# Structured output for programmatic use
papi ask "question" --format evidence-blocks
```

## MCP Tools (if available)

For quick retrieval without full RAG:
- `leann_search(index_name, query, top_k)` — fast semantic search
- `retrieve_chunks(query, index_name, k)` — PaperQA2 chunks with citations

Check available indexes: `leann_list()` or `list_pqa_indexes()`

## Output

RAG answers include:
- Synthesized response
- Citations with page/section references
- Confidence indicators

For general CLI commands, see `/papi`.

Signals

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Information

Repository
hummat/paperpipe
Author
hummat
Last Sync
3/12/2026
Repo Updated
3/11/2026
Created
1/26/2026

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