Leafly Strain Scraper is an MCP server that extracts structured cannabis strain data from Leafly.com following a standardized methodology. It implements both regex-based and LLM-powered extraction techniques to collect 66 data points per strain including cannabinoids, terpenes, effects, and flavors. The server handles batch processing with rate limiting, provides fallback mechanisms for missing data, and exports results in CSV or JSON format. Built with Node.js and the Firecrawl API, it requires an API key for authentication and is designed for researchers, developers, and cannabis industry professionals who need reliable, normalized strain information.
暂无评论. 成为第一个评论的人！
登录以参与讨论
Highlight AIScrape a single page with format selection (markdown, HTML, screenshots), custom actions, and content filtering
Discover all URLs on a website and generate a site map
Recursively crawl a website with depth and page limits
Scrape multiple URLs concurrently with queue-based processing
Poll the status of an in-progress batch scrape job
Poll the status of an in-progress crawl job
Search the web and return scraped content from results
LLM-powered structured data extraction using a caller-defined JSON schema
Multi-step research workflow that scrapes, synthesizes, and reports on a topic
Extract standardized cannabis strain data (cannabinoids, terpenes, effects, flavors, interactions)
Find function definitions across Python, JavaScript, and TypeScript files
Full-text search across all code files in a directory tree
Generate a tree-view representation of the project directory
Parse and analyze project dependency manifests
Discover React and React Native component definitions
Generate text using the DeepSeek Reasoner model (optimized for complex reasoning)
Condense text into a summary
Stream text generation with chunked output
Generate text using a caller-specified DeepSeek model variant
Process documents: summarize, extract entities, or analyze sentiment
Query JSON data using JSONPath expressions with array operations
Filter JSON arrays by field conditions (equality, range, pattern matching)
Persist query results to disk for later retrieval
Diff two JSON datasets and report structural/value differences
