This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
mcp-recall compresses MCP tool outputs (94 KB → 3.5 KB · 96%) and stores full results in SQLite for retrieval — up to 30x more tool calls per session for heavy MCP workloads. - sakebomb/mcp-recall
Hello!
I built mcp-recall to solve the problem of MCP token chewing with Claude Code (also other coding systems).
I saw that MCP tool output adds up quickly. A snapshot, a large API pull, a few of those, and half an hour in your context window is full. My session started needed compaction mid-task. What stood out to me: Claude Code already offloads its built-in tools to disk, but MCP tool output just gets cut off at ~25k tokens and dropped. That was the gap I wanted to close.
So mcp-recall catches MCP output before it hits the window, keeps the full copy locally in SQLite, and hands Claude a short summary instead. When it needs the details, it pulls back exactly what it needs. There is no need in re-running the tool.
Coming from security, keeping it local mattered to me: nothing leaves your machine, no outside service, no real dependencies. It's deterministic too. no second model in the loop deciding what to keep.
I built it for my own work, but figured it could be useful for others running long MCP sessions. If you do, I'd like to hear what tends to eat your context the most.
Really interesting idea. Curious—what was the moment that convinced you MCP context needed its own product instead of becoming another feature inside existing MCP clients?
About MCP-Recall on Product Hunt
“Keeps MCP tools' output from filling your context”
MCP-Recall was submitted on Product Hunt and earned 6 upvotes and 3 comments, placing #55 on the daily leaderboard. mcp-recall compresses MCP tool outputs (94 KB → 3.5 KB · 96%) and stores full results in SQLite for retrieval — up to 30x more tool calls per session for heavy MCP workloads. - sakebomb/mcp-recall
MCP-Recall was featured in Open Source (68.7k followers), Developer Tools (517.5k followers), Artificial Intelligence (475.9k followers) and GitHub (41.4k followers) on Product Hunt. Together, these topics include over 234k products, making this a competitive space to launch in.
Who hunted MCP-Recall?
MCP-Recall was hunted by Jonathan Tomek. 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.
Want to see how MCP-Recall stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.