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Context Mode

315 KB of MCP output becomes 5.4 KB in Claude Code

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Every MCP tool call dumps raw data into Claude Code's 200K context window. A Playwright snapshot costs 56 KB, 20 GitHub issues cost 59 KB. After 30 minutes, 40% of your context is gone.I built an MCP server that sits between Claude Code and these outputs. It processes them in sandboxes and only returns summaries. 315 KB becomes 5.4 KB.It supports 10 language runtimes, SQLite FTS5 with BM25 ranking for search, and batch execution. Session time before slowdown goes from ~30 min to ~3 hours.MIT licensed, single command install:/plugin marketplace add mksglu/claude-context-mode/plugin install context-mode@claude-context-modeBenchmarks and source: https://github.com/mksglu/claude-context-modeWould love feedback from anyone hitting context limits in Claude Code.

HN · launched Feb 25, 2026 · 84 upvotes (top 13%) · 0 views

Niche: model context protocol tools · 465 launches, 13 in the last 7 days ▼ -24% · Explore this niche →

Category and tags

  • Horizontal
  • Dev tools
  • Developer
  • AI feature
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes This is a standard MCP proxy middleware that intercepts verbose tool execution payloads, compresses or parses them inside a local container/sandbox, and returns condensed context to the LLM.

Discussion

20 comments analyzed.

Competitors mentioned: Tantivy (BM25 search engine), Context7, Playwright, GitHub MCP servers

Concerns raised: WebFetch hook doesn't trigger reliably (known bug in older versions), Database doesn't persist across sessions, Token counting is estimated (bytes/4), not actual tokenizer, No explicit raw mode toggle for full output, Lossy compression risk—missing information on first query

Feature requests: Add diagram showing data flow and implementation architecture, Persistent cross-session indexing with Tantivy for scalability, Dedicated PII redaction layer (regex-based sensitive data masking), Benchmark performance on smaller models vs. larger context-constrained ones (SWE-bench), Actual token counting instead of byte-based estimation

Competitors

Other products that read as similar to this one : 501 launches clear the similarity bar, closest 8 shown.

Attention rank: #90 of 502 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 111 days after the earliest competitor.

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