Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Description from the maker (original English)
Governed managed-endpoint ops — login-storm & drift analysis, 13 MCP tools with audit/budget/undo.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"endpoint-aiops": {
"command": "uvx",
"args": [
"endpoint-aiops"
]
}
}
}Run this in your terminal
claude mcp add endpoint-aiops -- uvx endpoint-aiopsPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"endpoint-aiops": {
"command": "uvx",
"args": [
"endpoint-aiops"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"endpoint-aiops": {
"type": "stdio",
"command": "uvx",
"args": [
"endpoint-aiops"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account AIops-tools, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
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It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.13.0) reached the registry 8 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Spec Driven Development, Remote Desktop Commander, sync. labs
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
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Audit availability: Real writes require a committed
pendingaudit row and stop before contacting the platform if storage is unavailable. Reads and previews may continue with a warning; new audit rows store outcome summaries rather than full responses.
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.
Two signature analyses, plus the guarded reads and writes around them:
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.endpoint-aiops mcp or endpoint-aiops-mcp): 13 tools (10 read, 3 write), every one wrapped with the bundled @governed_tool harness.~/.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).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).endpoint assign-profile, endpoint reboot) require double confirmation and support --dry-run.| Category | Tools | Count | R/W |
|---|---|---|---|
| Overview | overview | 1 | read |
| Inventory | endpoint_list, endpoint_get, endpoint_health_score | 3 | read |
| Sessions | session_list, login_storm_analysis | 2 | read |
| Drift | drift_report, patch_status, patch_compliance | 3 | read |
| Remediation | endpoint_assign_profile | 1 | write (high) |
endpoint_reboot | 1 | write (medium) | |
| Undo | undo_list | 1 | read |
undo_apply | 1 | write (medium) |
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.
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.
null, never as "" — the key is always present, so a missing patch level cannot be mistaken for a blank one.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.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.
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.
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.
Every operation — MCP and CLI — passes through the bundled @governed_tool harness. It records; it does not authorize (see above).
~/.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.ENDPOINT_RUNAWAY_MAX=0; optional hard ceilings via ENDPOINT_MAX_TOOL_CALLS / ENDPOINT_MAX_TOOL_SECONDS.risk_level; it gates nothing.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.
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.
| Dialect | Transport | Auth | Status |
|---|---|---|---|
generic (default) | /api/v2.0 on 443 | static Bearer API key | Neutral placeholder — not a real vendor API. Useful only once you describe your server's paths in a dialect: block. |
igel-ums | /umsapi/v3 on 8443 | HTTP Basic login → JSESSIONID cookie | Documented-but-unverified dialect for IGEL UMS (IMI). This is not a claim that IGEL is supported — see Status. |
targets:
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.
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 IGEOnly the beginning is shown; read the rest in the repo