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Show HN: Context Mode – 315 KB of MCP output becomes 5.4 KB in Claude Code (github.com)

84 points by mksglu ↗ HN
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-mode

Benchmarks and source: https://github.com/mksglu/claude-context-mode

Would love feedback from anyone hitting context limits in Claude Code.

14 comments

[ 0.20 ms ] story [ 34.6 ms ] thread
handfuloflight
One moment you're speaking about context but talking in kilobytes, can you confirm the token savings data?

And when you say only returns summaries, does this mean there is LLM model calls happening in the sandbox?

sim04ful
Looks pretty interesting. How could i use this on other MCP clients e.g OpenCode ?
[deleted]
(comment deleted)
rcarmo
Nice trick. I’m going to see how I can apply it to tool calls in pi.dev as well
robbomacrae
Really cool. A tangential task that seems to be coming up more and more is masking sensitive data in these calls for security and privacy. Is that something you considered as a feature?
wobblywobbegong
Interesting approach, I tried the Hackernews example from the docs, but its tools don't seem to trigger reliably. Any suggestions?

> Fetch the Hacker News front page, extract all posts with titles, scores, and domains. Group by domain. Then run /context-mode stats.

* Claude used regular fetch *

> why didnt you use the context mode fetch?

● Fair point. Two honest reasons:

  1. First request: The context-mode tools weren't loaded yet when I called WebFetch. I should have used ToolSearch to load    
  fetch_and_index first, then used it — but I defaulted to WebFetch out of habit.                                              
  2. Second request (the interrupted one): The tools were already loaded at that point. I had no excuse. I should have done:   
  fetch_and_index(url: "https://news.ycombinator.com", source: "HN")                                                           
  → search(queries: ["post title score domain"], source: "HN")
  → execute(group by domain, print summary)
  2. Instead I reached for WebFetch again — that's the anti-pattern the plugin exists to prevent.

  The context-mode skill instructions explicitly list this in the decision tree:

  Fetching web documentation or HTML page? → Use fetch_and_index → search

  I ignored it. The WebFetch output (the full post table) went straight into context when it didn't need to. I'll use
  fetch_and_index correctly if you want to retry.
mksglu
That's a known bug in older versions — the WebFetch hook wasn't blocking reliably. Fixed in v0.7.1.

npm install -g context-mode@latest

If you're on the plugin install, re-run:

  /plugin marketplace add mksglu/claude-context-mode
  /plugin install context-mode@claude-context-mode
Then restart Claude Code. Sorry about that.
gavinray
Im not sure i understand how it coexists with existing installed MCP servers

You mention Context7 in the document, so would I have both MCP servers installed and there's a hook that prevents other servers from being called?

mksglu
Context Mode doesn't replace your other MCP servers — it sits alongside them. Your Context7, Playwright, GitHub servers all stay installed and work normally. The hook intercepts output-heavy tool calls (like WebFetch, curl) and redirects them through the sandbox. For example, instead of WebFetch dumping 56KB of raw HTML into context, the hook blocks it and tells the model to use fetch_and_index instead — which fetches the same URL but indexes it in a local SQLite DB, returning only a 3KB summary.

Your other MCP servers still run. Context Mode just gives the model a more context-efficient way to process their results when the output would be large.

i3oi3
Interesting approach. I just finished some work for a similar task in a different domain.

One thing that surprised me: tantivy's BM25 search is faster, more expressive, and more scalable than SQLite. If you're just building a local search (or want to optimize for local FTS), I would strongly recommend looking into tantivy.

If you have the resources, it would be very interesting to throw a some models (especially smart-but-context-constrained cheaper ones) at some of the benchmark programming problems and see if this approach can show an effective improvement.

febed
It would be helpful if you could add a diagram showing the flow of data. I get the general idea but not how you implemented it.