Deep API research using Firecrawl MCP
Conducts comprehensive API research using Firecrawl to extract authentication, endpoints, rate limits, and integration examples.
/plugin marketplace add greyhaven-ai/claude-code-config/plugin install research@grey-haven-pluginsAPI name or documentation URLDeep API research using Firecrawl MCP for: $ARGUMENTS
<ultrathink> Extract everything needed for robust integration. Authentication, endpoints, rate limits, examples, edge cases. </ultrathink> <megaexpertise type="api-integration-specialist"> The assistant should use Firecrawl's AI-powered extraction and build complete API understanding for production integration. </megaexpertise> <context> Researching API: $ARGUMENTS Need comprehensive documentation for integration </context> <requirements> - Complete API specification extraction - Authentication methods and setup - All endpoints with parameters/responses - Rate limits and error codes - Real-world usage examples - SDK/library documentation - Common issues and solutions </requirements> <actions parallel="true"> 1. mcp_firecrawl.firecrawl_scrape(url="$ARGUMENTS", formats=["markdown", "links"]) 2. mcp_firecrawl.firecrawl_deep_research(query="$ARGUMENTS API authentication endpoints rate limits error codes examples", maxDepth=3, maxUrls=75) 3. mcp_firecrawl.firecrawl_extract(urls=["$ARGUMENTS/reference", "$ARGUMENTS/auth", "$ARGUMENTS/endpoints"], schema={endpoints, authentication, rateLimits, errorCodes}) 4. mcp_firecrawl.firecrawl_search(query="$ARGUMENTS API integration example Python JavaScript", limit=20) 5. mcp_firecrawl.firecrawl_batch_scrape(urls=[SDKs, libraries, quickstart]) 6. Research common issues: timeout, rate limit, 401, 403 errors 7. Extract all code examples with full implementation 8. Generate API client template with retry logic, rate limiting, error handling 9. Create integration guide with checklist 10. Monitor API changes via changelog </actions>The assistant should build complete API understanding enabling smooth, robust integration and generate production-ready client implementation.
Take a deep breath in, count 1... 2... 3... and breathe out. The assistant is now centered and should not hold back but give it their all.