May 2026 performance summary for the Firecrawl product suite. Delivered high-value scraping, API, monitoring, and billing improvements across firecrawl/firecrawl, firecrawl-firecrawl-mcp-server, and firecrawl/firecrawl-docs. Focused on data quality, reliability, and cost awareness to drive business value for customers using automated scraping workflows.

April 2026 saw focused delivery across API scraping, experimental query improvements, SDK enhancements, and reliability hardening. Notable features include API Scrape DirectQuote with a custom model to improve quote extraction in the API scrape/query pipeline; a consolidated Query Experiment with iterative model and deployment updates across multiple commits; .NET SDK parsing support enabling first-class ingestion for .NET artifacts; API Native stabilization through patched Calamine and related dependency fixes to improve build and runtime reliability; and a new Maximum Timeout for Concurrency Queue Jobs to give operators explicit latency control and improve system reliability. Additionally, groundwork was laid for Local File Parsing via the Firecrawl API in the MCP server and ongoing dependency hygiene including Rust SDK lockfile updates. These changes collectively improve data accuracy, shorten time-to-value for new data sources, and raise overall reliability and cross-language support.

March 2026 delivered measurable performance gains, reliability improvements, and targeted documentation updates across three Firecrawl repositories. Key features delivered include: (1) Performance and reliability improvements for GCS jobs and PDF cache retrieval in firecrawl/firecrawl, with stronger error handling and removal of unnecessary checks; (2) Documentation enhancements for scrape browser session endpoints in firecrawl-docs, clarifying execution/deletion flows and renaming endpoints for scraping jobs. Major bugs fixed include: (3) API test suite reliability improvements for self-hosted deployments in mendableai/firecrawl, conditioning test execution on TEST_SELF_HOST and flag-controlled runs; (4) Avgrab service stability and error handling, including extended timeouts via a custom agent, improved JSON handling and caching, and MapFailedError for mapController. Additionally (5) Dependency update: Firecrawl JS SDK upgraded to 4.18.1 for latest fixes and compatibility. Overall impact: faster GCS/PDF processing, more reliable cross-environment testing, clearer error reporting, and an improved developer experience through updated docs and SDK. Technologies demonstrated: performance tuning, robust error handling, test orchestration for multi-environment deployments, API/documentation discipline, and dependency upgrades.

February 2026 monthly summary focusing on delivered business value, major technical milestones, and core skill adoption across two repositories. Highlights include enhanced security posture in CI, improved observability through origin-aware logging, and a UX routing uplift for browser sessions via an interactive live view URL. These changes reduce risk, accelerate debugging, and improve end-user routing experiences.

January 2026 monthly summary for mendableai/firecrawl. Delivered key enhancements and maintenance that improve reliability, scalability, and developer productivity. Key features and fixes delivered: - Rate Limiting Enhancements for Search and Scraping Modes: Implemented dynamic rate limiting for search mode, refactored the rate limiter, and added scraping mode support to manage request rates. (Commits: e32c694a1bf3492533f6dcf22486e86a15ee387d; 04828ba0fbfac6605dde7fa58a1e00595fb2ce3b; e7edc9797d34c535769a1623d05045208893c080) - Remove hasAnyResults to fix fire_engine_search_v2 response validation bug: Simplified behavior by removing hasAnyResults due to a validation bug. (Commit: 9ada44ec8b0addb46817e3fbd88b963db5e0f20d) - Technical Debt Cleanup and Test Maintenance: Removed outdated caching in the extraction service, streamlined the test suite, and updated the test lockfile for consistent dependencies. (Commits: 8ef9ee6b85833e5f66e0d751cd213611fa1fca85; 20b2f5f79b860399c4e297722937855c490b0250; 723851ca9eb5a34f4b7e26c0f29bc692f879eca8) Overall impact and accomplishments: - Improved crawl throughput stability and reliability under variable load through dynamic rate limiting. - Reduced error surfaces by aligning API responses with valid expectations (removing hasAnyResults). - Achieved a cleaner, more maintainable codebase with deterministic test runs and dependencies, enabling faster iteration and safer deployments. Technologies/skills demonstrated: - Python refactoring and rate limiter design - API stability improvements and response validation debugging - Test suite optimization, dependency locking, and cache/CI hygiene - Clear commit hygiene and documentation of changes