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.
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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.
