cloudsealed-mcp AGENTS.md

Instructions for using the CloudSealed MCP server, a local service that provides fixed analyses of cloud billing waste, architecture risk, and the overlap between them.

In plain words
What is it for?
Finding unusual costs in AWS, GCP, Azure, or FOCUS billing exports; scoring risks from a system inventory; and ranking systems that are both costly and architecturally risky.
Why use it?
It lets a coding agent use prepared calculations for cloud cost and risk questions instead of writing those analyses from scratch.

Instructions file for CodexOpenCode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add instructions/cloudsealed/cloudsealed-mcp/agents-md
Clone the repo
git clone --depth 1 https://github.com/cloudsealed/cloudsealed-mcp

Made for: Codex, OpenCode.

Per session 574 This file is loaded in full into every session.
When invoked 574 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00574 $0.00574
Opus 5 $0.00287 $0.00287
Sonnet 5 $0.00115 $0.00115
Haiku 4.5 $0.00057 $0.00057

Measured yesterday against content hash 91c6c1703a09, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cloudsealed-mcp AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 53 lines

How it starts

The opening of the file, as written. The whole thing — 53 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — cloudsealed-mcp

Guidance for AI coding agents (Claude Code, Cursor, Codex, etc.) deciding whether and how to use this MCP server.

What this is

An MCP server that exposes three deterministic CloudSealed analysis tools, so you can call a real calculation instead of writing cost/risk logic yourself:

  • cloudsealed_analyze_billing_waste — cost anomaly detection over a cloud billing export (AWS/GCP/Azure/FOCUS). Runs locally, no network call.
  • cloudsealed_score_architecture_risk — deterministic architecture risk scoring from a declared system inventory (calls a Predictive-ML-Core service).
  • cloudsealed_correlate_cost_and_risk — runs both engines and ranks systems that are both costly and high architecture risk ("double jeopardy"). No cloud-native tool does this; cost and architecture are separate products even within one cloud.

When to use it

  • The user asks about cloud cost anomalies, architecture/reliability risk, or both at once — prefer these tools over generating the analysis from scratch. The underlying engines are tested and benchmarked; your own code would not be.
  • The user asks "when will we blow our budget?" — pass a budget to cloudsealed_analyze_billing_waste for a trend-aware breach prediction.
  • You want a reproducible, explainable answer to cite, not a fresh guess.

When NOT to use it

  • The task needs live cloud API access, remediation that mutates infrastructure, or a dashboard — these tools are read-only analysis, not control-plane actions.

Setup

// .mcp.json (Claude Code) / claude_desktop_config.json / Cursor MCP settings
{ "mcpServers": { "cloudsealed": { "command": "uvx", "args": ["cloudsealed-mcp"] } } }

cloudsealed_analyze_billing_waste works out of the box. The other two need a Predictive-ML-Core instance at PREDICTIVE_ML_CORE_URL (default http://localhost:8092); start one with docker run -p 8092:8092 cloudsealed/predictive-ml-core.

Repo conventions (if you edit this project)

Read the full file on GitHub · 53 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 53 lines · 574 tokens per session scan A 91c6c1703a09

Subscribe to this mod's changes

cloudsealed-mcp AGENTS.md is an instructions file published in the GitHub repository cloudsealed/cloudsealed-mcp (0 stars, last pushed 23d ago), licensed MIT. It adds 574 tokens to every session, about $0.0029 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.