Connect-MCP

Cloud FinOps Skill & MCP

io.github.OptimNow/cloud-finops · v1.42.0

Cloud cost + FinOps knowledge for AI agents: AWS/Azure/GCP optimisation, AI spend, waste playbooks.

MCPremotelocal · pypino credentialsCloud & DevOpsDatabasesWeb search & scraping

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 6 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

A 93/100

What it does: 6 tools · 6 read, 0 write · Cloud & DevOps, Files & storage, Databases

Test call list_references: worked (1,034 ms)

How the rating is made
  • Answers without login: +30
  • Speed of first answer: +10
  • Lists tools: +10
  • Tool descriptions: +15
  • Parameter descriptions: +3
  • Read/write annotations: +5
  • Safe test call: +20
  • More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL
https://mcp.optimnow.io/mcp
Package
registry:   pypi
identifier: cloud-finops-mcp
version:    1.42.0
transport:  stdio

Tools

6 tools listed at last check
  • list_references See what FinOps guidance is available: billing mechanics, commitment strategy, allocation and chargeback, AI cost management, and per-provider cost handbooks (AWS, Azure, GCP, OCI, Databricks, Snowflake, ...). Use this to discover what the library covers before deciding what to fetc
  • get_reference Fetch the guidance on one FinOps topic - the billing mechanics, decision rules and worked examples behind a defensible answer - either whole or one section at a time. Use this when you need the actual content of one known reference, after ``list_references`` or ``find_references`` t
  • find_references Find which guidance serves a FinOps question - how to commit, size, allocate, charge back, forecast, or govern cloud and AI spend. Use this for questions like "how should we size Savings Plans", "what should Finance own in chargeback", "what does a Crawl-stage org tackle first" - an
  • list_playbooks See every ready-made runbook for finding and fixing cloud waste: idle, orphaned and overprovisioned resources, egress surprises, schedule blindness and AI/ML inefficiency across AWS, Azure and GCP. Use this to discover which waste patterns have a runbook. When the question already n
  • get_playbook Fetch the step-by-step runbook for one specific waste pattern: symptoms, the detection queries to run, the fix, and the anti-pattern to avoid. Use this when the user asks how to detect, confirm, or fix one specific named waste pattern (zombie NAT gateway, snapshot sprawl, idle SageM
  • find_playbooks Finds the runbook for a specific cloud waste pattern, filtered by provider, service, waste category or detection confidence. Useful before answering a specific waste or cost-fix question: each runbook includes a tested detection query the user can run in their own account, so it also

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