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Kontext CLI

Credential broker for AI coding agents in Go

Details

External ID
47765374
Source
HN
Company
—
Product
Kontext CLI
Website domain
github.com
Launched
April 14, 2026
Cohort
—
Upvotes
70
Upvotes percentile
0.8669665809768637
Tags
—
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

We built the Kontext CLI because AI coding agents need access to GitHub, Stripe, databases, and dozens of other services — and right now most teams handle this by copy-pasting long-lived API keys into .env files, or the actual chat interface, whilst hoping for the best.The problem isn't just secret sprawl. It's that there's no lineage of access. You don't know which developer launched which agent, what it accessed, or whether it should have been allowed to. The moment you hand raw credentials to a process, you've lost the ability to enforce policy, audit access, or rotate without pain. The credential is the authorization, and that's fundamentally broken when autonomous agents are making hundreds of API calls per session.Kontext takes a different approach. You declare what credentials a project needs in a .env.kontext file: GITHUB_TOKEN={{kontext:github}} STRIPE_KEY={{kontext:stripe}} LINEAR_TOKEN={{kontext:linear}} Then run `kontext start --agent claude`. The CLI authenticates you via OIDC, and for each placeholder: if the service supports OAuth, it exchanges the placeholder for a short-lived access token via RFC 8693 token exchange; for static API keys, the backend injects the credential directly into the agent's runtime environment. Either way, secrets exist only in memory during the session — never written to disk on your machine. Every tool call is streamed for audit as the agent runs.The closest analogy is a Security Token Service (STS): you authenticate once, and the backend mints short-lived, scoped credentials on-the-fly — except unlike a classical STS, we hold the upstream secrets, so nothing long-lived ever reaches the agent. The backend holds your OAuth refresh tokens and API keys; the CLI never sees them. It gets back short-lived access tokens scoped to the session.What the CLI captures for every tool call: what the agent tried to do, what happened, whether it was allowed, and who did it — attributed to a user, session, and org.Install with one command: `brew install kontext-dev/tap/kontext`The CLI is written in Go (~5ms hook overhead per tool call), uses ConnectRPC for backend communication, and stores auth in the system keyring. Works with Claude Code today, Codex support coming soon.We're working on server-side policy enforcement next — the infrastructure for allow/deny decisions on every tool call is already wired, we just need to close the loop so tool calls can also be rejected.We'd love feedback on the approach. Especially curious: how are teams handling credential management for AI agents today? Are you just pasting env vars into the agent chat, or have you found something better?GitHub: https://github.com/kontext-dev/kontext-cli Site: https://kontext.security

Enrichment

Theme
AI agent frameworks and developer tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
credential management for ai coding agents
Manually corrected
False

Could you build this?

Yes It is a command-line interface written in Go that acts as a secure local credential broker or proxy for development secrets. A solo developer can vibe-code this using standard Go CLI libraries, local encrypted storage (or OS keyring integration), and basic token generation.

Discussion

17 comments analyzed.

Competitors mentioned: Bitwarden (self-hosted password management), Tailscale Aperture (contextual authorization), OneCLI (credential management), System keyrings (macOS, Linux, Windows)

Concerns raised: Server-side secret storage makes it DOA for many users, Agent could persist or leak API keys from environment, Memory inspection vulnerability if agent runs as same user, Unclear custody model and credential storage location, Support for non-OIDC services unclear

Feature requests: Self-hosted deployment option, Support for services without OIDC, Work with direct HTTP calls (curl) not just scripts, eBPF-based approach to inject tokens without abstraction layer, Integration with coding/AI agents

Competitors

Other products that read as similar to this one — 367 launches clear the similarity bar, closest 8 shown.

Attention rank: #59 of 368 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 164 days after the earliest competitor.

Other launches for this product

Same idea, different domain

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