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).
Product upvotes vs the next 3
Waiting for data. Loading
Product comments vs the next 3
Waiting for data. Loading
Product upvote speed vs the next 3
Waiting for data. Loading
Product upvotes and comments
Waiting for data. Loading
Product vs the next 3
Loading
MCP-Recall
Keeps MCP tools' output from filling your context
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.
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
On the analytics side, MCP-Recall 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 MCP-Recall performed against the three products that launched closest to it on the same day.
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.
For a complete overview of MCP-Recall including community comment highlights and product details, visit the product overview.
Jonathan Tomek