AgentPeek vs A.I.G (AI Infra Guard): Features, Pricing & Which Is Better (2026)
A side-by-side comparison of AgentPeek and A.I.G (AI Infra Guard) — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
AgentPeek
Tran Huu Hoang
Mac menu-bar app that puts Claude Code and Codex into the Mac notch to watch sessions, answer prompts, track tokens, and manage local dev servers.
Key features
- Notch & Menu-bar Integration: Embeds live Claude Code and Codex sessions into the Mac notch and menu bar for immediate, always-available access without switching windows.
- Live Session Viewer: Displays real-time agent activity and conversation streams so users can watch multi-agent interactions as they occur and inspect agent behavior.
- Interactive Prompt Handling: Surfaces permission prompts and allows users to answer, approve, or modify prompts directly from the menu-bar interface to control agent inputs.
- Token Usage Tracking: Monitors and reports token consumption per session or agent, helping developers manage costs and debug token-related issues.
- Local Dev Server Management: Provides controls to start, stop, and monitor local development servers tied to agent workflows, streamlining local testing and iteration.
- Local-first Privacy Model: Designed to run locally on the user’s Mac to minimize external data exposure and give users control over where agent data is processed.
- Release Log & Versioning: Public release log (changelog) with incremental releases (0.1.x series) so users can track features, fixes, and updates over time.
- Multi-agent Visualization: Integrates with multi-agent setups (per GitHub repo) to visualize interactions across agents for debugging and analysis.
- Embed Claude Code and Codex sessions in the Mac notch and menu bar
- Live session replay and real-time visualization
- Permission prompts and response handling
- Token usage tracking and metrics
- Manage and monitor local development servers
- Local-first storage: session data stays on device
- Live visualization of Claude Code and Codex agent sessions in the Mac notch and menu bar
- Interactive permission prompts allowing users to answer agent prompts from the menu bar
- Token usage tracking and reporting for monitored agent sessions
- Management and monitoring of local development servers associated with agents
- Real-time dashboard for multi-agent orchestration and activity inspection
- Local-first architecture (runs on user's Mac rather than cloud-hosted by default)
- Distributed via a one-time license purchase
Best for
- Observing Multi-Agent Workflows: Watch real-time exchanges between agents to debug coordination issues or verify agent decision paths without opening developer consoles.
- Rapid Prompt Approval: Approve, modify, or answer permission prompts from the menu bar to speed up interactive sessions with Claude Code or Codex during development.
- Token Cost Monitoring: Track token usage during experiments to identify costly prompts or optimize prompt engineering for lower consumption.
- Local Development Management: Start and manage local dev servers used by agents directly from the app, simplifying local testing and iteration cycles.
- Desktop AI Command Center: Keep an always-on control surface for AI coding assistants (Claude Code, Codex) accessible from the Mac notch for quick coding help.
- Agent Behavior Auditing: Capture and inspect live session logs to audit agent outputs, confirm compliance with expected behavior, or reproduce bugs.
- Monitor and debug multi-agent interactions during local development
- Quickly view and respond to agent prompts from the Mac menu bar/notch
- Track token usage and costs while iterating on agents
- Run and control local dev servers for agent workflows
- Provide lightweight agent observability during demos or testing
- Monitor and debug multi-agent workflows spawned by Claude Code or Codex in real time
- Track and audit token consumption during agent runs for cost and performance analysis
- Answer permission or confirmation prompts quickly from the menu bar without switching windows
- Manage local development servers used by agent systems during development and testing
- Provide a lightweight dashboard for agent orchestration and visibility on macOS
A.I.G (AI Infra Guard)
Tencent Zhuque Lab
Tencent's open-source AI red teaming platform for scanning agents, agent skills, MCP servers and AI infrastructure, plus LLM jailbreak evaluation.
Key features
- Agent Skills Scan: Audits agent skill packages against a nine-category risk taxonomy aligned with the public SkillTrustBench T01-T09 classification, including detection of .pyc bytecode bypasses and charset smuggling.
- MCP Server Scan: Inspects MCP servers for threats such as tool poisoning, credential exfiltration and command injection, with tool whitelisting to prevent remote code execution during dynamic scanning.
- AI Infrastructure Vulnerability Scanning: Checks deployed AI components against a library that has grown to roughly 130 components and over 2,000 CVE rules, covering frameworks such as llama.cpp.
- Jailbreak Evaluation: Runs single-turn jailbreak operators plus multi-turn attack techniques including Many-Shot, PAIR, GOAT and ActorAttack to measure a model's resistance.
- Agent Scan with OWASP Coverage: Assesses running agents using OWASP-derived skills and web exfiltration detection, with a dedicated agent red team skill for comprehensive assessment.
- Standalone Scanner CLIs: skill-scan, mcp-scan and agent-scan each install as an independent command-line tool so scans can be wired directly into enterprise CI/CD pipelines.
- Docker Deployment with Web UI: Deploy the full platform with Docker on 4GB+ RAM and reach the web interface at localhost:8088, or use a one-click install script or a source build.
- AI Security Skill Market: A catalog of official security scanning skills, with the frontend fully open-sourced and integration available from OpenClaw chat via the aig-scanner skill.
Best for
- Pre-Deployment Agent Audit: Scan an internally built agent and its skill bundle for prompt injection, exfiltration and privilege risks before it is released to staff.
- MCP Supply Chain Review: Vet third-party MCP servers for tool poisoning and credential exfiltration before connecting them to production assistants.
- CI/CD Security Gate: Run skill-scan as a standalone CLI on every pull request so risky agent skills fail the build rather than shipping.
- Model Safety Benchmarking: Measure how a deployed LLM holds up against single and multi-turn jailbreak techniques before and after guardrail changes.
- AI Infrastructure Patch Triage: Inventory AI serving components and match them against the CVE rule library to prioritise which hosts need patching.
- Security Research and Reporting: Use the open scan engines and SkillTrustBench alignment as a reproducible basis for internal or published AI security research.