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