Enterprises block AI coding tools over data leakage fears. But we know MCP-based AI tools' productivity. Individuals move ahead — organizations can't keep up. leeh: use AI freely outside, push results into your internal network through a one-way pipeline. Ed25519 signed, SHA-256 verified, scanned, quarantined. Optional AI intent analysis and admin approval gate. Open source. Python/FastAPI. Apache 2.0.
Hi Product Hunt!
I'm the solo developer behind leeh.
The problem: I work at a large enterprise where all external
LLM access is blocked for security reasons. Fair enough —
data leakage is real. But we already know how productive
MCP-based AI coding tools are. Individuals move ahead,
organizations can't keep up.
So I asked: what if you use AI tools freely on a separate
network, and push only the results in — safely?
That's leeh. A one-way push pipeline. Not a dev tool —
a delivery tool. It works with whatever AI coding tool
you prefer (Claude Code, Gemini CLI, Copilot, Cursor).
Key design decisions:
- Fail-closed: if a scanner is missing, code is blocked (not skipped)
- Server-side policy: the gateway enforces rules, not the client
- Human gate: optional admin approval prevents AI agents
from pushing unlimited code autonomously
Would love feedback on the security architecture.
Happy to answer any questions!
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