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With AI, Everyone is a Dev. EveryDev.ai © 2026
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    3. ctrlrun
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    ctrlrun

    Autonomous Systems
    Featured

    An open-source Python library that acts as an execution safety layer for AI agents, checking every action against your rules before it runs and blocking wrong, restricted, or malicious actions.

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    At a Glance

    Pricing
    Open Source

    Fully open-source under Apache-2.0. Free to use, modify, and distribute.

    Engagement

    Available On

    Windows
    Web
    API
    SDK
    CLI

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Autonomous SystemsHuman-in-the-Loop TrainingAgent Frameworks

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    PusharySapienX AgentOSVigilator
    Developer
    CTRLRunNew York, United States

    Listed Sep 2026

    About ctrlrun

    ctrlrun is an open-source Python library that sits between an AI agent's decision to act and the call that actually executes. It checks every outbound action against a YAML policy before it runs, routes sensitive actions to a human for approval, and blocks forbidden ones entirely. Released under Apache-2.0, it runs in production on a single SQLite file or on Postgres across multiple hosts, with no external service required.

    What It Is

    ctrlrun is an execution safety layer — a programmable checkpoint that intercepts consequential AI agent actions before they reach your systems. The core idea is that a tool being callable is not permission to call it with any arguments: ctrlrun reads the arguments about to leave your process and answers one of three things — let it run, ask a human, or stop it cold. It is a Python library installed via pip install ctrlrun, and integration is as simple as a @ctrlrun.protect decorator on the function that has the consequence, plus a YAML policy file that names the rules.

    The Seven-Step Execution Boundary

    Every protected call, regardless of how it arrives, passes through the same pipeline before reaching your systems:

    • Normalize — the call becomes a canonical Action with a SHA-256 hash
    • Decide — authority is checked first (may this principal propose this?), then policy (how much autonomy does this action get?); silence is never permission
    • Approve — a human answers against the exact action hash; the approval is single-use, expires, and matches nothing but that exact action
    • Reserve — the effect key is claimed in one atomic write; a second caller on another process or host is refused
    • Execute — your code runs; only NotExecuted means FAILED, every other exception means AMBIGUOUS
    • Resolve — an AMBIGUOUS effect keeps its key and refuses a retry until a human or a reconcile hook says what happened
    • Record — a portable JSON receipt is written for every attempt, refusals included, chained to the receipt before it

    Three Ways to Integrate

    ctrlrun offers three integration paths depending on what you have:

    • @protect decorator — wraps any Python function in this process: a raw model call, a LangChain tool, a hand-rolled loop, or a cron job; needs nothing beyond pip install ctrlrun
    • MCP gateway — places every guarantee in front of an MCP tool server in any language, with no changes to the agent or server code; installed with pip install "ctrlrun[gateway]"
    • Framework adapters — routes an approve decision through a framework's own interrupt (LangChain, LangGraph, OpenAI Agents SDK) so a human answers where they already answer

    Key Guarantees

    The library enforces six core guarantees, each present since early versions:

    • Approval binding — an approval is bound to the exact action hash; mutated or replayed approvals are refused
    • One effect, once — one logical effect key happens at most once, across threads, processes, and hosts
    • Unknown is not failed — a lost reply is AMBIGUOUS, never FAILED, and blocks a blind retry
    • Fail closed — an unknown action, missing policy, or missing principal is denied by default
    • Authority and delegation — every principal needs a grant; delegation cannot widen one; a grant bounds the total, including optional rolling-window budgets since v0.9
    • Receipts — every executed action leaves a portable JSON receipt of who, what, and outcome, chained by hash

    Update: v0.12.2

    The latest release is v0.12.2, published on 2026-09-15, available on PyPI for Python 3.11 through 3.14. The project's changelog tracks features by version: the @protect decorator and core guarantees landed in v0.1; the MCP gateway and webhook approvals in v0.2; authority and delegation in v0.3; the ctrlrun verify command and verified badge in v0.4; framework adapters in v0.5; Postgres support, receipt chaining, policy versioning, and the control registry in v0.6; and budget-bounded grants in v0.9. The repository lists 6,248 tests, with every requirement mutation-tested, and 32 guarantees checkable in any user's own setup via ctrlrun verify.

    Architecture and Deployment

    State lives in SQLite by default — a single file with no server and no ops, production-grade on one host. Pointing it at Postgres (pip install "ctrlrun[postgres]") enables the same guarantees across multiple hosts, graded by the same test suite. The enforcement kernel is fully open source under Apache-2.0, and releases carry PyPI provenance attestations from GitHub Actions. Two products — ctrl ai agents and ctrl payments — are documented on the ctrlrun site as running on this kernel and crediting it on every page.

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    Pricing

    OPEN SOURCE

    Open Source

    Fully open-source under Apache-2.0. Free to use, modify, and distribute.

    • Full enforcement kernel
    • SQLite and Postgres backends
    • All guarantees: approval binding, one effect once, AMBIGUOUS, fail closed, authority, receipts
    • @protect decorator, MCP gateway, framework adapters
    • Operator CLI

    Capabilities

    Key Features

    • Per-action YAML policy (allow / approve / deny per action and argument)
    • Approval binding — approvals bound to exact action hash; mutations void the approval
    • One effect, once — atomic effect key reservation across threads, processes, and hosts
    • AMBIGUOUS outcome — unknown results block blind retries until a human resolves
    • Fail closed — unknown actions, missing policy, or missing principal are denied
    • Authority and delegation — grants, delegation chains, and rolling-window budgets
    • Portable JSON receipts chained by hash for every action, including refusals
    • @protect decorator for Python functions
    • MCP gateway for tool servers in any language
    • Framework adapters for LangChain, LangGraph, and OpenAI Agents SDK
    • Operator CLI (approve, deny, resolve, inspect, count)
    • Webhook approvals (e.g., Slack)
    • Reconciliation hook for AMBIGUOUS effects
    • OpenTelemetry export (one span per action)
    • Observe mode — records what would have been blocked without blocking
    • ctrlrun verify — runs guarantee catalogue against your policy and store
    • Verified badge for GitHub Actions CI
    • SQLite (single host) and Postgres (multi-host) backends
    • Versioned schema with forward-only migrations
    • Recovery after crash — dead worker effects stay AMBIGUOUS until resolved
    • Receipt chain integrity — alteration detected and named
    • Policy versioning — every receipt names the policy hash that decided it
    • Control registry — name compliance controls satisfied by an action
    • Data scope — label arguments by data class and condition rules on labels
    • Runtime delegation — principals narrow their own grants at runtime
    • MCP server exposing documentation search

    Integrations

    LangChain
    LangGraph
    OpenAI Agents SDK
    Slack (webhook approvals)
    MCP (Model Context Protocol)
    Postgres
    SQLite
    OpenTelemetry
    Cursor
    Claude Code
    ChatGPT
    Codex
    GitHub Actions
    PyPI
    API Available
    View Docs

    Ratings & Reviews

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    Developer

    CTRLRun Team

    CTRLRun builds ctrlrun, an open-source execution safety layer for AI agents that intercepts consequential actions before they reach production systems. The project enforces per-action policies, human-in-the-loop approvals, and at-most-once execution guarantees across any Python-based agent workflow. The enforcement kernel is Apache-2.0 and powers two downstream products — ctrl ai agents and ctrl payments — that credit it on every page. Releases carry PyPI provenance attestations from GitHub Actions.

    New York
    Read more about CTRLRun Team
    WebsiteGitHub
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