Agent skill · research science · k-dense-ai
bgpt-paper-search
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.
Why this skill is useful
Provides structured data extraction from full-text scientific papers that the AI wouldn't reliably generate on its own.
What it needs
Requires bgpt account access. About 2k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
BGPT Paper Search Overview BGPT is a remote MCP server that searches a curated database of scientific papers built from raw experimental data extracted from full-text studies. Unlike traditional literature databases that return titles and abstracts, BGPT returns structured data from the actual paper content — methods, quantitative results, sample sizes, quality assessments, and 25+ metadata fields per paper. When to Use This Skill Use this skill when: Searching for scientific papers with specific experimental details Conducting systematic or scoping literature reviews Finding quantitative results, sample sizes, or effect sizes across studies Comparing methodologies used in different studies Looking for papers with quality scores or evidence grading Needing structured data from full-text papers (not just abstracts) Building evidence tables for meta-analyses or clinical guidelines Setup BGPT is a remote MCP server — no local installation required. Configure it in your agent's MCP settings before use; this skill instructs the agent to call the searchpapers MCP tool and does not enable MCP access by itself. Claude Desktop / Claude Code Add to your MCP configuration: npm (alternative) Usage Once the BGPT MCP server is configured, call its searchpapers tool via the agent's MCP interface (not via Bash): The server returns structured results including: Title, authors, journal, year, DOI Methods: Experimental techniques, models, protocols Results: Key findings with quantitative data Sample sizes: Number of subjects/samples Quality scores: Study quality assessments Conclusions: Author conclusions and implications Pricing Free tier: 50 searches per network, no API key required Paid: $0.01 per result with an API key from bgpt.pro/mcp
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/bgpt-paper-search