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flatten-mcp
Resume Claude Code sessions 61% lighter, losslessly
Claude Code compacts long sessions into a lossy summary. flatten-mcp moves bulky tool output to a backup, keeps every prompt verbatim, and resumes the session at a lower token count. 340k->133k on a real run. Reversible, MIT.
Maker here. Claude Code stores each session as a JSONL event log, and near the
context limit it compacts the whole thing into a summary that regularly drops the
detail you needed two hours later.
flatten-mcp does the opposite. In long sessions the bulk of the tokens is tool
output (file reads, command logs, base64 screenshots), not your conversation. So it
moves that output above a size threshold into a backup copy next to the session and
leaves a small reference marker in place. Every prompt and reply stays verbatim, the
session resumes as itself, and any moved blob can be pulled back by id on demand.
On a real session that went 340,071 -> 132,800 tokens (61% lighter). Fully
reversible, crash safe (atomic writes plus a self-cleaning backup), Claude Code only,
local stdio, no telemetry, MIT. Happy to answer anything about the session format or
the safety model.
About flatten-mcp on Product Hunt
“Resume Claude Code sessions 61% lighter, losslessly”
flatten-mcp was submitted on Product Hunt and earned 4 upvotes and 1 comments, placing #156 on the daily leaderboard. Claude Code compacts long sessions into a lossy summary. flatten-mcp moves bulky tool output to a backup, keeps every prompt verbatim, and resumes the session at a lower token count. 340k->133k on a real run. Reversible, MIT.
On the analytics side, flatten-mcp competes within Open Source, Developer Tools, Artificial Intelligence and GitHub — topics that collectively have 1.1M followers on Product Hunt. The dashboard above tracks how flatten-mcp performed against the three products that launched closest to it on the same day.
Who hunted flatten-mcp?
flatten-mcp was hunted by Shaya Shaviv. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of flatten-mcp including community comment highlights and product details, visit the product overview.
Shaya Shaviv