Kontext Cli

Kontext Cli

Runtime authorization for AI agents that checks every tool call before it executes.

71/100Safe BetFree · from $149/moFreemium

Kontext's observe-before-enforce workflow is a rare combination of safety and developer speed, and the local Kestrel classifier is a legit innovation—fast and accurate. It's a solid choice if you run Claude Code, Codex, or Cowork, but the narrow agent support and local-install requirement mean it's not for everyone. Try the Starter plan in a sandbox.

Verified 5d ago · liveness 71/100 · cite: rightaichoice.com/tools/kontext-cli

Best for
  • Security teams enforcing least privilege for AI agent tool calls
  • Developers running Claude Code, Codex, or Cowork who want guardrails without slowing down
  • Platform teams integrating agents with production systems needing granular policy control
  • Compliance teams needing structured, exportable audit trails for agent actions
Not ideal for
  • Teams needing a fully managed SaaS-only solution (requires local install)
  • Organizations looking for prompt-injection detection (focuses on runtime authorization)
  • Users who want a no-code policy editor (policy defined via code/config)
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IntermediateFor a single developer, you can install the daemon with one command and have it running in observe mode within 5 minutes. For a team rollout, expect 1-2 hours to configure policies, test in observe mode, and transition to enforce. No code changes are needed, so the main time investment is defining your policy layers.CLI · WebAPI availableVerified 5d ago
Pricing
Free · from $149/mo
FreemiumFree tier3 plans3 hidden costs
Learning curve
Intermediate
For a single developer, you can install the daemon with one command and have it running in observe mode within 5 minutes. For a team rollout, expect 1-2 hours to configure policies, test in observe mode, and transition to enforce. No code changes are needed, so the main time investment is defining your policy layers.
Runs on
CLIWeb
API available · 3 integrations
Who it's for
Security engineer at a mid-size startupPlatform engineer integrating agents with production systemsCompliance officer at a financial services firm
Live sentiment
Is Kontext Cli actually worth it?

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  • Real pros & cons from real users
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Skip it if

Skip Kontext if your team doesn't use Claude Code, Codex, or Cowork, or if you need a fully managed SaaS-only solution without local installation.

The 30-second take
Biggest gripe

The $149/mo Pro plan charges per month, but you may need the $499/mo Scale plan for higher volume and longer retention, which can be a big jump in cost.

Price reality

Kontext's pricing is freemium: $0 Starter for developers, $149/mo Pro, $499/mo Scale. Compared to gateway proxy solutions that charge per token or per seat, Kontext's flat monthly pricing is more predictable for high-volume agent use. However, for small teams needing advanced features, the jump from $149 to $499 might be steeper than competitors.

In short

Kontext Cli — Runtime authorization for AI agents that checks every tool call before it executes. Best for Security teams enforcing least privilege for AI agent tool calls, Developers running Claude Code, Codex, or Cowork who want guardrails without slowing down, Platform teams integrating agents with production systems needing granular policy control. Free to start; paid plans from $149/mo.

What's new in Kontext Cli

Checked 3 days ago

Across the latest 8 updates: 2 feature updates, 2 launches and 4 news mentions.

LaunchBlog·6 days agoNewest

How to Really Secure an AI Agent (2026 Guide)

Guide covers sandbox containment, brokered credentials, enforced egress, runtime authorization, and tamper-evident audit logs for agents.

NewsBlog·15 days ago

Should You Care About Prompt Injection? (Probably.)

Agents read untrusted content and turn it into actions. Sanitize → detect → enforce at tool boundaries to make that speed survivable.

FeatureBlog·15 days ago

The API Key is Dead: A Blueprint for Agent Identity in the age of MCP

Replaces static API keys with OAuth 2.0 for MCP agents using scoped tokens, Dynamic Client Registration, delegation, and federation.

NewsBlog·15 days ago

The 5 Agent Security Failures Your IAM Stack Can't See

Identifies five authz failures for autonomous systems, from unauthenticated access to credential sprawl, and how to address them.

NewsBlog·15 days ago

How to Keep a Secret: Why Personal AI Assistants Like OpenClaw Are a Security Nightmare

Breakdown of OpenClaw's three failure modes: unauthenticated access, credential sprawl, and prompt injection, with practical fixes.

LaunchBlog·15 days ago

Announcing Kontext

Kontext gives AI agents proper identity, scoped access, and audit trails. One SDK, one line: kontext.require().

NewsBlog·15 days ago

Agent Intent - No One Knows What It Means, But It's Provocative

Argues runtime authorization should evaluate action safety instead of verifying intent, with layered controls for unsafe tool use.

FeatureBlog·15 days ago

Kestrel: A local classifier for evaluating the cyber risk of agent tool calls

Local classifier screens agent tool calls in ~22 microseconds, beating seven frontier LLMs by ~0.40 F1 on ShellRisk-Bench.

What people actually say about Kontext Cli — is it worth it?

We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.

6 mentions across 3 sources (Hacker News, GitHub, Lemmy) · researched Jul 3, 2026.

67% positive33% critical
Recurring strengths
  • +Runtime enforcement prevents risky tool calls before execution.
  • +Structured audit trails provide full visibility into agent actions.
  • +Local-first mode allows testing without blocking (observe mode).
  • +Short-lived scoped credentials reduce the risk of leaked secrets.
  • +Open-source enables community inspection and customization.
Recurring frustrations
  • Only Claude Code is supported as an agent workflow currently.
  • Limited community size means fewer shared policies and integrations.
  • No public benchmarks on performance overhead yet.
  • Configuration may be complex for non-security engineers.
  • Very few user reviews available to assess real-world reliability.
Patterns worth knowing
Runtime authorization is a critical missing piece in agent security
Seen on Hacker News
Kontext is complementary to other agent safety tools
Seen on Hacker News
Current secret management practices (copy-pasting API keys) are risky
Seen on Hacker News
Learning curve
beginnerProductive in ~10 minutes

Viability Score

71/100
Safe Bet

How well maintained and how widely used is Kontext Cli? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this

Recent activity
90
Traction
77
Site health
95
User sentiment
67
What the vendor publishes
40

Last calculated: September 2026

How we score →

Key Features

  • Runtime authorization for AI agent tool calls
  • Deterministic policy for hard boundaries
  • Local risk judge scores ambiguous actions
  • Kestrel local classifier screens tool calls in ~22 microseconds
  • Observe mode backtests policy without blocking
  • Enforce mode blocks destructive commands
  • Human approval for risky actions
  • Policy layering by org, group, user, agent, repo, branch
  • Payload capture configurable (omitted, summary, full)
  • Redaction of tool calls and payloads on-machine
  • Unified console for sessions, decisions, devices
  • Filter audit trail by agent, user, repo, policy
  • Exportable audit trail with attribution
  • Local daemon install with one command
  • No code changes or gateway required

About Kontext Cli

FreemiumIntermediateAPI availableCLI · Web

Kontext is an open-source runtime authorization layer that hooks every tool call from Claude Code, Codex, and Cowork before it runs, enforcing policy in milliseconds with a local risk judge and deterministic rules. It installs via a one-command daemon, requires no code changes or gateway, and evaluates decisions on the machine so developer speed stays intact. Destructive commands like rm -rf on protected paths are blocked before reaching the shell, and risky actions wait for a human yes. Kontext pairs deterministic policy with a unique local classifier, Kestrel, which screens tool calls in ~22 microseconds and beats seven frontier LLMs on ShellRisk-Bench. Policies layer across org, group, user, agent, repo, and branch, with payload capture configurable as omitted, summary, or full—redacting tool calls and payloads locally before anything streams to the dashboard. Deployment starts in observe mode, backtesting policy against real agent traffic without blocking; when the would-deny log matches intent, you flip to enforce. A unified console streams sessions, decisions, and devices for filtering by agent, user, repo, or policy, with an exportable, attributed audit trail. Kontext covers endpoints (developer machines), cloud (agent applications with real credentials), and SaaS (agents inside SaaS tools). Unlike gateway proxies or prompt-injection-focused tools, Kontext's local-first enforcement avoids performance hits and code changes—a practical fit for teams committed to these specific agents. Pricing is freemium: Starter at $0, Pro at $149/mo, and Scale at $499/mo.

Behind the Verdict

Kontext is the first tool we've seen that treats agent authorization like a networking firewall—policy checked at the call, not at the prompt. The local-first design is the right call: by evaluating every tool call on the machine, it keeps latency low and avoids the bottleneck of a gateway. The observe mode is a genuinely smart onboarding trick—you can backtest your policies against real traffic without breaking anything, then flip to enforce when you're confident. Where it really shines is teams running Claude Code, Codex, or Cowork on developer machines. If you've ever had an agent run rm -rf in the wrong directory or push to a protected branch, Kontext's deterministic blocks are exactly what you need. The audit trail is a compliance gift: every decision is attributed and exportable, so you can show who ran what, where, and why it was allowed. The Kestrel classifier is the headline grabber—22 microseconds per call, beating seven frontier LLMs on ShellRisk-Bench. That's a real, measurable advantage over any cloud-based classifier, where round-trip latency would slow agents down. But it's worth noting the benchmark is specific to shell commands; we'd like to see more diverse coverage. Kontext's biggest constraint is agent support. It only works with three agents. If your team uses a different tool, you're out of luck—no plugin SDK, no generic MCP hook. That's a hard limit that might push larger orgs to wait or look elsewhere. Pricing is reasonable for what you get, but the Pro tier at $149/mo might be steep for small teams. The free Starter plan covers developers on their own machines, so you can pilot it without spending. The Scale tier is aimed at higher volume and longer retention—if you need enterprise custom identity or deployment support, you'll have to talk

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Real-world workflow fit

Concrete scenarios for the personas Kontext Cli actually fits — and what changes day-one when you adopt it.

Security engineer at a mid-size startup

You roll out Kontext to a team of 10 developers using Claude Code. You start in observe mode, monitor the would-deny logs, tune policies, then switch to enforce. Within a day, you catch a developer trying to rm -rf a protected path, and the tool blocks it, saving your team from a potential disaster.

Outcome: You have a working runtime authorization layer that blocks destructive commands and provides a full audit trail, all without slowing down developers.

Platform engineer integrating agents with production systems

You need to give an AI agent scoped credentials to access GitHub APIs. Using Kontext, you define a policy that restricts commands to git fetch and git push to specific branches, and require human approval for force pushes. You test in observe mode, then enforce.

Outcome: Agents operate with least privilege, and risky operations like force pushes require human sign-off, reducing the risk of accidental damage.

Compliance officer at a financial services firm

You need to prove to auditors that AI agent actions are controlled and logged. You deploy Kontext across dev machines, set payload capture to full, and export audit trails showing who ran what, where, and why it was allowed.

Outcome: You have structured, exportable evidence of all agent actions, satisfying compliance requirements without manual oversight.

Use Cases

  • Enforce least privilege by blocking destructive shell commands before execution.
  • Issue scoped credentials to AI agents for GitHub or cloud APIs without exposing long-lived keys.
  • Audit every tool call with structured traces showing actor, session, tool, and policy decision.
  • Test agent authorization policies in observe mode before enforcing them in production.
  • Escalate ambiguous credential requests to human approval via ask decision.
  • Integrate runtime authorization into CI/CD pipelines for AI-coded changes.

Models Under the Hood

Claude CodeCodexCowork

as of 2026-08-27

Limitations

  • Kontext is a runtime authorization tool for AI agents, not an underlying AI model provider.
  • It supports Claude Code, Codex, and Cowork tool calls, but other agents may require additional configuration.
  • The tool enforces policy on tool calls and may require setup for different agent environments.
  • Managed team features may be subject to plan availability.

as of 2026-08-20

Verification history

We have re-verified Kontext Cli 6 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.

  1. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  2. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  3. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  4. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  5. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
  6. re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it

Free to cite with attribution — this page re-verifies continuously.

12-month cost

Project the real annual outlay, including the implied monthly cost when only an annual tier is published.

Annual total
Free
Over 12 months
Effective monthly
Free
Billed monthly

Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.

Plans compared

For each published Kontext Cli tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.

Starter

$0/mo

Ideal for

Solo developer or small team securing their own machines with basic agent guardrails, starting at $0.

What this tier adds

Free entry point with local daemon, observe and enforce modes, policy layering and audit trail for individual use.

Pro

$149/mo

Ideal for

Teams rolling agents out across the org, needing higher volume and longer retention, at $149/mo.

What this tier adds

Adds higher volume, longer retention, and unified console for sessions and decisions, compared to Starter.

Scale

$499/mo

Ideal for

Large enterprises requiring extended data retention and org-wide deployment, at $499/mo.

What this tier adds

Adds extended retention and scaled deployment for org-wide coverage, compared to Pro.

Hidden costs & gotchas

What the public pricing page doesn't put in bold. Captured from pricing-page footnotes, contract terms, and recurring complaints.

  • The $149/mo Pro plan charges per month, but you may need the $499/mo Scale plan for higher volume and longer retention, which can be a big jump in cost.
  • If you need custom identity, deployment, or volume requirements, you'll have to contact sales for enterprise pricing, which could be unpredictable.
  • The free Starter plan is limited to developers securing agents on their own machines, so you might need to upgrade quickly as you scale beyond personal use.

Where the pricing makes sense

The company stage and team size where Kontext Cli's pricing actually pencils out — and where peers do it cheaper.

Kontext's pricing is freemium: $0 Starter for developers, $149/mo Pro, $499/mo Scale. Compared to gateway proxy solutions that charge per token or per seat, Kontext's flat monthly pricing is more predictable for high-volume agent use. However, for small teams needing advanced features, the jump from $149 to $499 might be steeper than competitors.

Setup time & first value

How long it actually takes to get something useful out of Kontext Cli — broken out by persona, not the marketing-page minute.

For a single developer, you can install the daemon with one command and have it running in observe mode within 5 minutes. For a team rollout, expect 1-2 hours to configure policies, test in observe mode, and transition to enforce. No code changes are needed, so the main time investment is defining your policy layers.

Switching to or from Kontext Cli

How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.

Migrating in
  • From manual shell command monitoring: You can start using Kontext in observe mode to see what agents would do, then switch to enforce, gradually replacing ad-hoc oversight.
Migrating out
  • To a gateway proxy solution: If you need centralized enforcement across many agents or non-supported agents, you may migrate to a gateway-based approach, but you'll lose the low-latency local enforcement.

Integrations

Claude CodeCodexCowork

Resources & Guides

Tutorials & Learning

Official links

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Frequently Asked Questions

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