Deepcon – Get the most accurate context for coding agents
I got frustrated watching Claude Code fail at using modern APIs (ask it about GPT-5 and it says it doesn't exist). Existing solutions like Context7 dump thousands of tokens of irrelevant docs into context. So I built DeepCon. How it works: - Crawled 10,000+ official docs using agentic browser automation and structured them hierarchically - Query decomposer breaks down requests, searches in parallel, then merges only relevant context - Returns just what's needed: 2.4x fewer tokens than Context7 Results on our benchmark: DeepCon achieved 90% accuracy vs Context7's 65% on real-world tasks with…
What it does
In the maker’s words, at launch
I got frustrated watching Claude Code fail at using modern APIs (ask it about GPT-5 and it says it doesn't exist). Existing solutions like Context7 dump thousands of tokens of irrelevant docs into context. So I built DeepCon. How it works: - Crawled 10,000+ official docs using agentic browser automation and structured them hierarchically - Query decomposer breaks down requests, searches in parallel, then merges only relevant context - Returns just what's needed: 2.4x fewer tokens than Context7 Results on our benchmark: DeepCon achieved 90% accuracy vs Context7's 65% on real-world tasks with modern AI frameworks. Without any MCP context, Sonnet 4.5 scored 0%. It's an MCP tool. You can just plug it into Claude Code/Cursor and suddenly they understand the latest libraries and APIs. GitHub benchmark: https://github.com/opactorai/context-bench Service: https://deepcon.ai Built this because I needed it. Would love feedback!
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