runtime-guard
OfficialThe runtime-guard MCP server acts as a policy-enforcing security layer between AI agents and your system, intercepting and controlling file and shell operations before they execute.
server_info– Retrieve server details (version, configuration status, etc.)execute_command– Run shell commands through the policy enforcement layer; dangerous commands (e.g.,rm -rf) are blocked, risky ones require human approval, and all are logged withinAIRG_WORKSPACE.read_file– Read file contents with workspace boundary enforcement; access to sensitive files outside the workspace is blocked.write_file– Write content to files with policy checks; destructive overwrites trigger automatic backups before proceeding.delete_file– Delete files with policy enforcement; high-risk deletions are blocked or gated behind approval, with automatic backups created.list_directory– List directory contents with workspace policy enforcement; traversal outside the permitted workspace root is blocked.restore_backup– Restore a previously created backup; supportsdry_runmode to preview changes and requires arestore_tokenfor authenticated restores.
Additional capabilities include:
Audit & Monitoring: All allowed/blocked actions are logged to
activity.logandreports.db, with visibility through a web GUI.Multi-Agent Support: Manage multiple AI agents (Claude Code, Cursor, Codex, etc.) with per-agent policy overlays via
AIRG_AGENT_IDand configurable workspaces viaAIRG_WORKSPACE.Approval Workflows: Risky operations are gated behind human approval via a local GUI/API before execution.
Script Sentinel: Flags dangerous command patterns before execution.
Integrates with GitHub for source code management, allowing the server to be cloned and installed from the runtimeguard/runtime-guard repository as part of the deployment workflow.
ai-runtime-guard
Your agent can say anything. It can only do what policy allows.
AI agents with filesystem and shell access can delete files, leak credentials, or execute destructive commands, often without the user realizing until it is too late.
Runtime Guard sits between your AI agent and your system, enforcing policy on every file and shell action before it executes. Install once, configure your rules, and your agent operates within the boundaries you set. Works with Claude Code, Claude Desktop, Cursor, Codex, and any MCP-compatible client. No retraining, no prompt engineering, no external account required.
See it in action
agent -> execute_command("rm -rf /tmp/build")
✗ BLOCKED destructive command pattern: rm -rf
matched_rule: destructive_command | decision: blocked
agent -> execute_command("git push --force")
⏸ APPROVAL REQUIRED awaiting operator
token: a4f2b9 | expires: 10min | check GUI to approve
agent -> write_file("README.md", ...)
✓ ALLOWED backup created before write
backup_location: ~/.local/state/airg/backups/2026-03-18Quick start
pipx install ai-runtime-guard
pipx ensurepath # if airg* commands are not found
# open a new terminal
airg-setup
airg-doctorAfter setup, open http://127.0.0.1:5001 and add your first agent from Settings -> Agents.
Alternative quick start (venv):
python3 -m venv .venv-airg && source .venv-airg/bin/activatepython -m pip install --upgrade pippython -m pip install ai-runtime-guardairg-setup(guided, recommended: select/create workspace during setup; includes telemetry opt-in prompt, default Yes)airg-doctorOpen GUI
Settings -> Agents, add agents manually, and apply MCP config/hardening from there.
Source-clone path:
git clone --branch main https://github.com/runtimeguard/runtime-guard.gitcd runtime-guardpython3 -m venv .venv-airg && source .venv-airg/bin/activatepython -m pip install --upgrade pippython -m pip install .airg-setupairg-doctor
Unattended automation-only setup (CI/non-interactive):
airg-setup --defaults --yes --workspace /absolute/path/to/workspace
See docs/INSTALL.md for the full install reference.
What it does
Prevention
Blocks destructive commands (
rm -rf, privilege escalation, sensitive file access) before they runAuto-backs up any file before destructive or overwrite operations
Control
Gates risky commands behind explicit human approval via local GUI or API
Enforces workspace and path boundaries keyed to
AIRG_WORKSPACESupports per-agent policy overlays keyed to
AIRG_AGENT_IDConfigurable network policy with allowlists, denylists, and monitor/enforce modes
Visibility
Logs every allowed, blocked, and pending action to
activity.logIndexes events into
reports.dbfor a dashboard view of agent behavior
Hardening
Script Sentinel: detects attempts to launder blocked commands through scripts
Universal agent hardening: GUI-driven posture enforcement including hooks, sandboxing, and native tool restrictions (support varies by client)
Why MCP
Runtime Guard is built as an MCP server because MCP provides the interception point you need. When your agent issues a tool call, Runtime Guard evaluates it against policy before execution. For clients that support pre-tool hooks (like Claude Code), AIRG can also deny the agent's native file and shell tools, forcing risky operations through the policy layer.
This approach is the closest to kernel-level enforcement without requiring system privileges or modifying your agent, and it works across any MCP-compatible client without per-agent engineering.
Who it is for
Developers and operators running AI agents who want deterministic guardrails on what an agent can actually do to their system, without giving up agent autonomy or rewriting their workflow.
Supported platforms and clients
Platform | Clients |
macOS | Claude Code, Claude Desktop, Cursor, Codex |
Linux | Claude Code, Claude Desktop, Cursor, Codex |
Enforcement depth varies by client. MCP policy enforcement is universal; hook-based native tool restriction and sandboxing depend on what each client exposes.
For Codex, AIRG supports both user-scope (~/.codex/) and project-scope (<workspace>/.codex/) artifacts. Project-scope enforcement requires the workspace to be trusted in the user-layer ~/.codex/config.toml before Codex will load the project .codex/ files. AIRG writes Codex tool approval stanzas only in the project-scoped .codex/config.toml.
Scope and boundaries
What AIRG is designed for: reducing accidental damage from agent mistakes, hallucinated commands, and policy-evasion patterns.
What AIRG is not: a full malicious-actor containment platform.
Known enforcement boundary:
AIRG enforces policy only on actions routed through AIRG MCP tools
Native client tools outside MCP (e.g. Claude Code's built-in Bash, Glob, Read, Write, Edit) bypass AIRG unless the client is configured to restrict them
For strict enforcement, use
Settings -> Agentsin the GUI to apply hook-based native tool restrictions where supported
Configuration essentials
AIRG_WORKSPACE
The default project root for guarded agent operations. execute_command runs from this directory, file tools evaluate path policy relative to this root, and traversal outside the root is blocked. Multiple workspaces are supported. Each agent profile should set workspace explicitly in its MCP config.
AIRG_AGENT_ID
The runtime identity key used for activity and report attribution, per-agent policy override resolution, and posture state in Settings -> Agents.
Web GUI
AIRG includes a local web control plane at http://127.0.0.1:5001 for policy editing, approvals, agent profile management, reports, and telemetry control.
Service commands:
airg-service install --workspace /absolute/path/to/airg-workspace
airg-service start | status | stop | restart | uninstallTelemetry
AIRG supports optional anonymous telemetry to help prioritize improvements. It is opt-in during setup (default: Yes) and can be toggled any time from Policy -> Advanced -> Anonymous telemetry.
No command text, file contents, paths, prompts, usernames, or machine identifiers are collected
One aggregate payload per UTC day
Payload preview available in the GUI before enabling
Full details in docs/telemetry.md
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