Endpoint AIops

Endpoint AIops

Disclaimer: Community-maintained open-source project. Not affiliated with, endorsed by, or sponsored by any endpoint-management vendor. Product and trademark names belong to their owners. MIT licensed.

Governed AI-ops for managed-endpoint fleets — thin clients, VDI endpoints, and other centrally-managed devices — with a built-in governance harness: unified audit log, token/runaway budget guard, undo-token recording, and descriptive risk tiers. Vendor-neutral: it talks to an endpoint-management server's REST API (Bearer auth) through a configurable dialect — see Dialects. Self-contained: no dependencies beyond httpx and the MCP SDK. The test suite is mock-based; the endpoint-management REST paths have not yet been exercised against a live management server — see docs/VERIFICATION.md.

What it does

Two signature analyses, plus the guarded reads and writes around them:

• Login-storm analysis — during a "everyone logs in at 9am" incident, detect the storm (bursts of concurrent logins in a sliding window) and rank the endpoints/users dragging login and boot times. Every flag is reported with its number, not a black-box verdict.
• Patch / config drift — find endpoints that have drifted from the fleet (outdated patch level, stray agent version, divergent OS build or config profile). With no declared baseline it derives one by fleet majority, so it works before a gold image exists.

What works

• CLI (endpoint-aiops ...): init, overview, endpoint list/get/assign-profile/reboot, session list/storm, drift report/patch, secret set/list/rm/migrate/rotate-password, doctor, mcp.
• MCP server (endpoint-aiops mcp or endpoint-aiops-mcp): 13 tools (10 read, 3 write), every one wrapped with the bundled @governed_tool harness.
• Encrypted credentials: the management-server API key lives in an encrypted store ~/.endpoint-aiops/secrets.enc (Fernet + scrypt) — never plaintext on disk. Unlock with a master password from ENDPOINT_AIOPS_MASTER_PASSWORD (MCP/CI) or an interactive prompt (CLI).
• Reversibility: endpoint_assign_profile (high risk) captures the prior profile and records an inverse "reassign the prior profile" undo descriptor. endpoint_reboot (medium risk) captures the prior online state for the audit record but declares no undo (a reboot has no safe inverse).
• Safety: state-changing CLI ops (endpoint assign-profile, endpoint reboot) require double confirmation and support --dry-run.

Capability matrix (13 MCP tools)

The analysis tools (login_storm_analysis, drift_report, patch_status, patch_compliance, endpoint_health_score) accept injected records for pure/offline analysis; endpoint_health_score and patch_compliance are injected-only, the others also pull live from a configured target.

What this tool does, and does not, decide

It delivers managed-endpoint operations — reads and writes — accurately and efficiently, and records every one of them. It does not decide whether a write is allowed to happen. That is the agent's judgement, or the permission of the account you connect it with: give it a management-console account or API token scoped to a read-only role and the writes fail at the server — the place that actually owns the permission.

So there is no read-only switch, no policy file, no approval gate to configure. The one thing the tool guarantees is that nothing is silent: every call, over MCP and over the CLI alike, lands an audit row in ~/.endpoint-aiops/audit.db, and reversible writes still capture their before-state and record an inverse where one exists.

Each tool declares a risk_level, kept in agreement with its [READ]/[WRITE] documentation tag by a test, and carried into the audit row as a descriptive tier — so a reviewer can see at a glance that a row was a high-risk write. It is a label, not a gate.

Running a smaller / local model? See agent-guardrails.md — it lists the guardrails this tool now enforces for you (so you don't spend prompt budget restating them) and gives a ready-made system prompt for what's left.

Payload conventions

• Absent is not empty. A field the management server did not report comes back as null, never as "" — the key is always present, so a missing patch level cannot be mistaken for a blank one.
• Capped lists announce themselves. Any list a limit can cut short is a truncation envelope: {"items": [...], "returned": N, "limit": L, "truncated": bool}, with truncated measured rather than inferred. Companion totals (driftedCount, behindCount, nonCompliantCount, stormCount, the health summary) are always the full, uncapped figures.

Quick start

As a Claude Code plugin

One install gives an agent both the skill and the MCP server:

/plugin marketplace add AIops-tools/marketplace
/plugin install endpoint-aiops@aiops-tools

The MCP server is fetched with uv and pinned to the package version this plugin declares, so an audit row can be traced back to the code that wrote it. Credentials are still configured with endpoint-aiops init — see below.

As an OpenClaw plugin

The same bundle is published on ClawHub, where one install delivers the skill and its MCP server together:

openclaw plugins install clawhub:@zw008/endpoint-aiops
openclaw skills info endpoint-aiops          # expect: Visible to model: yes

Restart the OpenClaw gateway afterwards so it loads the plugin. The MCP server is fetched with uv, pinned to this exact release, so uvx has to be on PATH — without it the skill still installs but reports Visible to model: no. Credentials are configured exactly as below.

As a CLI or standalone MCP server

uv tool install endpoint-aiops          # or: pipx install endpoint-aiops
endpoint-aiops init                     # wizard: add a target + store its API key (encrypted)
endpoint-aiops doctor                   # verify config, secrets, connectivity
endpoint-aiops overview                 # one-shot fleet health
endpoint-aiops session storm            # detect a login storm + slow contributors
endpoint-aiops drift report             # endpoints drifted from the fleet baseline

Run as an MCP server (stdio):

export ENDPOINT_AIOPS_MASTER_PASSWORD=...   # unlock secrets non-interactively
endpoint-aiops-mcp

Where that password then lives: an exported variable is readable by every process this shell starts and is recorded by shell history. On a shared or long-lived host, prefer the interactive prompt, or inject it from a secret manager for the life of the one command that needs it.

Governance

Every operation — MCP and CLI — passes through the bundled @governed_tool harness. It records; it does not authorize (see above).

• Audit — every call (params, result, status, duration, risk tier, and any operator-supplied approver/rationale) is logged to ~/.endpoint-aiops/audit.db (relocatable via ENDPOINT_AIOPS_HOME). The CLI writes the same row the MCP path does — there is no unaudited entry point.
• Runaway guard — a safety backstop, not an authorization gate: the same call hammered in a tight loop trips a circuit breaker so a stuck agent can't burn unbounded calls/time. Disable with ENDPOINT_RUNAWAY_MAX=0; optional hard ceilings via ENDPOINT_MAX_TOOL_CALLS / ENDPOINT_MAX_TOOL_SECONDS.
• Undo recording — reversible writes record an inverse descriptor built from the fetched before-state.
• Risk tier — a descriptive label on the audit row derived from risk_level; it gates nothing.

Scope

This is the IT-endpoint member of the AIops-tools family (governed AI-ops with audit + budget + undo + risk tiers). For OT / industrial edge (Modbus, OPC-UA, PROFINET, …) see the separate industrial-aiops line.

Dialects — which server are you actually pointing at?

A dialect is the management server's API shape: resource paths, response field names, the transport defaults (port + API base path), and how to authenticate. Set it per target in config.yaml; endpoint-aiops init asks for it and prints which one it configured.

targets:
  - name: ums1
    host: ums.example.local
    dialect: igel-ums        # IMI paths, port 8443, /umsapi/v3, Basic-login auth
    username: ums-admin      # UMS account; the password lives in secrets.enc
    scheme: https            # or 'http' for a reverse-proxied server
    verify_ssl: false        # self-signed lab UMS only

The generic default is not an IGEL configuration and never was: IGEL serves IMI at /umsapi/v3 on 8443, so a target left on the generic shape 404s on its first probe. That mismatch is why the preset exists.

Where a server genuinely has no such resource, the dialect says so rather than guessing a URL — IMI exposes no login/boot session resource, so session_list and login_storm_analysis on an igel-ums target return a teaching error naming the absent resource instead of calling an invented path.

A dialect selects the auth scheme too, not just paths — IMI rejects the static Bearer token the generic dialect sends, so it logs in with HTTP Basic at POST /umsapi/v3/login and carries the returned JSESSIONID cookie (once per connection, then cached). Because the scheme comes from the dialect, a credentials failure and a wrong-dialect failure are reported differently: a 401 names the scheme presented and, when the server sends a WWW-Authenticate challenge, the scheme it actually wants — so a dialect mismatch does not send you off rotating a perfectly good key.

⚠️ Note for IGEL specifically: a UMS account with too few permissions receives empty lists rather than a 403. endpoint-aiops doctor authenticates as a step separate from its reachability probe and warns when a successful login returns no endpoints, because "no devices" and "not allowed to see the devices" are otherwise indistinguishable.

Status

The test suite is mock-based. No dialect in this package has been exercised against a real management server, so this package does not claim support for any specific product — including IGEL.

• generic is a placeholder shape, not a vendor API.
• igel-ums is a documented-but-unverified dialect. Its paths and field aliases are modelled from IGEL's published IMI documentation; its auth scheme is documented in the IMI manual and matches what three independent real-world IMI clients do. Neither has been run against an appliance by this project — IGEL UMS has no free edition, so it cannot be verified on the maintainer's hardware.

Both are recorded as UNKNOWN-pending-live in docs/VERIFICATION.md, which ranks what a live run is most likely to find wrong and defines the checklist it must cover. If you have a UMS and run that checklist, the results are very welcome as an issue. Missing a capability or a server dialect? Open an issue or PR — contributions welcome.