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RZFL

AgentOps Guardian MCP

by RZFL

AgentOps Guardian MCP

Quick Install

Prerequisites:

  • Node.js 20.17.0 or newer with npm.

  • Git, only if you clone the repository.

  • Python 3 is optional. It is used only by npm run demo:inspector; the core MCP server, tests, and workflow demo run on Node.js.

  • No Docker, cloud service, external database, or API key is required for the local demo.

Install notes:

  • Keep network access enabled for npm install.

  • sqlite3 normally installs a prebuilt native package. If npm falls back to compiling it, install the standard native build tools for your OS and rerun npm install.

Fresh local setup:

git clone <repo-url>
cd agentops-guardian-mcp
npm install
npm run check
npm test
npm run build
npm run demo:workflow

If an AI coding agent is installing this project, ask it to run the same commands and stop before any git push, npm publish, or GitHub release command. A healthy install ends with demo:workflow returning status: "needs_user_approval".

MCP hosts should point to the built server:

{
  "mcpServers": {
    "agentops-guardian": {
      "command": "node",
      "args": ["C:/absolute/path/to/agentops-guardian-mcp/dist/index.js"]
    }
  }
}

On Windows, use absolute paths and escape backslashes if your MCP host requires JSON escaping.


Related MCP server: Architect-to-Product (A2P)

Capstone Summary

Track: Agents for Business
Problem: AI coding agents can make risky local changes without rollback.
Solution: MCP safety agent that reviews actions, checkpoints files, and restores workflow state.
Demo: guardian_run_workflow blocks unsafe writes, creates checkpoints, and guardian_restore_workflow restores files.
Course concepts: MCP, agent loop, skills/rules, security guardrails.

On-demand safety agent for AI coding workflows.

AgentOps Guardian MCP is a local-first Model Context Protocol server that helps developers inspect AI-agent workspaces, review risky actions, create rollback checkpoints, and restore files when an AI coding workflow goes wrong.

The project is designed for the Agents for Business track: it reduces the operational cost of using AI coding agents in real development teams.


Key Features

  • One-call agent workflow: guardian_run_workflow plans, inspects, scores, reviews a proposed action, checkpoints files, persists compact workflow state, and returns a compact decision.

  • Workflow rollback: guardian_restore_workflow restores all files checkpointed by a saved Guardian workflow.

  • Backup first: safe_checkpoint, restore_latest, and prepare_safe_edit remain direct recovery tools before risky edits.

  • Agent/MCP inspection: inspect_agent_environment_components reports local agents, MCP servers, skills, plugins, hooks, model providers, and app integrations.

  • Cheap by default: compact output, short in-memory inspector cache, no background daemon, no constant logging, and no automatic token-heavy summaries.

  • Security review: deterministic checks flag shell execution, file writes without approval, destructive commands, publishing commands, and secret-looking actions.


Architecture

The main loop is:

proposed action
  -> guardian_run_workflow
  -> plan
  -> inspect agent/MCP environment
  -> score and triage risks
  -> review proposed action
  -> create checkpoints
  -> persist workflow state
  -> return decision and next action

If the result is wrong:

guardian_restore_workflow(workflowId)
  -> read .agentops/workflows/<workflowId>.json
  -> restore all successful checkpoints

See docs/architecture.md for details.


Setup

Install dependencies and build:

npm install
npm run build

Run checks:

npm run check
npm test

Start the MCP server:

npm start

Main Tools

  • guardian_run_workflow — top-level agent workflow.

  • guardian_restore_workflow — restore all checkpointed files from a workflow.

  • safe_checkpoint — quick backup for one file.

  • restore_latest — restore the latest checkpoint for one file.

  • prepare_safe_edit — review an edit and checkpoint target files.

  • inspect_agent_environment_components — inspect local agent/MCP components.

  • score_agent_surface — compact risk score for the local agent surface.

  • triage_guardian_findings — group findings into must-fix, review, informational, and ignored buckets.

  • review_agent_action_plan — deterministic safety review for a proposed action.


Demo

Run the deterministic workflow demo:

npm run build
npm run demo:workflow

The demo creates a test file, proposes a risky shell action, runs the Guardian workflow, creates a checkpoint, persists workflow state, and returns needs_user_approval instead of executing the command.

For the live MCP test evidence, see docs/live-mcp-test.md.


Project Docs


Agent Instructions

To make another AI assistant use the Guardian workflow consistently, copy the relevant rules from AGENTS.md.example into that assistant's project rules file.

Recommended default:

Before risky file edits, call guardian_run_workflow.
Proceed only when the workflow decision is ready.
If the edit goes wrong, call guardian_restore_workflow with the workflowId.

Design Principles

  • Local-first.

  • On-demand only.

  • Deterministic checks before LLM interpretation.

  • Compact output by default.

  • No background monitoring.

  • No continuous event logging.

  • Rollback before risky action.


License

MIT. See LICENSE.

A
license - permissive license
-
quality - not tested
B
maintenance

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