paper-mcp
Use the Paper MCP server to fetch paper metadata, sections, figures, citations, and full-text context, then translate that context into structured outputs such as summaries, extraction tables, and implementation-ready notes. Trigger when a task involves paper links/DOIs/arXiv IDs, literature review, citation extraction, or Paper MCP setup and troubleshooting.
What this skill does
# Paper MCP Use the Paper MCP server for paper-driven research and implementation tasks. For setup and debugging details (env vars, config, verification), see `references/paper-mcp-config.md`. ## Paper MCP integration rules These rules define how to translate paper inputs into reliable outputs and must be followed for every paper-driven change. ### Required flow (do not skip) 1. Resolve the paper first (URL/DOI/arXiv/PMID) and fetch high-level metadata before requesting full text. 2. If the full response is large or truncated, fetch section-level context and work section-by-section. 3. Fetch a stable citation list before drafting any claims that depend on references. 4. If figures/tables are relevant, fetch those assets and capture captions prior to synthesis. 5. Only after metadata plus content context are collected, generate the user output (summary/table/notes/code-facing plan). 6. Validate all key claims against source excerpts before marking complete. ### Tool mapping rule - Paper MCP deployments may expose different tool names. - Start by listing available paper MCP tools, then map this workflow to equivalent tools in the current server. - If a required capability is missing (for example, no section fetch or no citation endpoint), note the limitation and continue with the best available fallback. ### Implementation rules - Treat paper MCP responses as source context, not final prose. - Keep outputs traceable: tie each important claim to a section, figure, or citation. - Distinguish evidence from inference clearly. - Preserve units, metrics, and dataset/task names exactly as written in source context. - Prefer concise structured output (tables/checklists) when comparing multiple papers. - For code-facing tasks, extract actionable constraints (input shapes, evaluation metrics, baseline numbers, reproducibility requirements). ### Quality rules - Do not invent citations, metrics, or section names. - Call out uncertainty when context is partial, truncated, or conflicting. - If two sources disagree, present both with scope and date/context differences. - Keep quoted text short and use paraphrasing for long passages. ## References - `references/paper-mcp-config.md` - setup, verification, troubleshooting, and input ID guidance. - `references/paper-tools-and-prompts.md` - tool mapping checklist and prompt templates for common paper workflows.
Related in AI Agents
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