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Meet Contextual
A local-first temporal context engine for your AI agents
Contextual is a local-first CLI/MCP daemon that gives any AI coding agent (Claude Code, Cursor, Copilot, and more) a persistent, structurally accurate memory of your codebase built from a real dependency graph and AST parsing, not text similarity or guesswork. 0 bytes of your code ever leave your machine. 5 mins to contextualise on 50k LOC, 94.5 ms median recall latency, so your AI tools finally know your code as well as you do.
Hi everyone — excited to bring Contextual to Product Hunt today.
Before this, I was freelancing on enterprise agentic AI and ML prediction systems. The same problem kept showing up: once an agent hit a real production codebase, it would confidently guess wrong about code it didn't understand, and I'd lose hours rewriting the same prompt just to get back to where I already was.
Contextual is a local daemon that gives any MCP-capable AI client (Claude Code, Cursor, Copilot, and more) a real, persistent memory of your codebase — built from an actual dependency graph and AST parsing, not text similarity.
Honest numbers: 5 mins to contextualise 50k LOC, 94.5ms median recall latency, 0 bytes of your code ever leave your machine. Median Recall@10 across 11 real repos is 85%, with a true range of 54–98% depending on the codebase.
It's $10/mo, proprietary, with a full-featured 14-day trial rather than a capped free tier — capping usage would mean tracking what you do locally, and the whole point is that we don't.
Built this to help developers ship faster. Would love your honest take, especially anything that surprises or breaks for you — thanks for checking it out!
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About Meet Contextual on Product Hunt
“A local-first temporal context engine for your AI agents”
Meet Contextual was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #130 on the daily leaderboard. Contextual is a local-first CLI/MCP daemon that gives any AI coding agent (Claude Code, Cursor, Copilot, and more) a persistent, structurally accurate memory of your codebase built from a real dependency graph and AST parsing, not text similarity or guesswork. 0 bytes of your code ever leave your machine. 5 mins to contextualise on 50k LOC, 94.5 ms median recall latency, so your AI tools finally know your code as well as you do.
Meet Contextual was featured in Productivity (659.6k followers), Developer Tools (518.5k followers) and Artificial Intelligence (477.4k followers) on Product Hunt. Together, these topics include over 356.3k products, making this a competitive space to launch in.
Who hunted Meet Contextual?
Meet Contextual was hunted by Aarjun Mahule . 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.
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Aarjun Mahule
Hi everyone — excited to bring Contextual to Product Hunt today.
Before this, I was freelancing on enterprise agentic AI and ML prediction
systems. The same problem kept showing up: once an agent hit a real
production codebase, it would confidently guess wrong about code it didn't
understand, and I'd lose hours rewriting the same prompt just to get back
to where I already was.
Contextual is a local daemon that gives any MCP-capable AI client (Claude
Code, Cursor, Copilot, and more) a real, persistent memory of your
codebase — built from an actual dependency graph and AST parsing, not text
similarity.
Honest numbers: 5 mins to contextualise 50k LOC, 94.5ms median recall latency,
0 bytes of your code ever leave your machine. Median Recall@10 across 11
real repos is 85%, with a true range of 54–98% depending on the
codebase.
It's $10/mo, proprietary, with a full-featured 14-day trial rather than a
capped free tier — capping usage would mean tracking what you do locally,
and the whole point is that we don't.
Built this to help developers ship faster. Would love your honest take,
especially anything that surprises or breaks for you — thanks for
checking it out!