_ registry / mcp http-sse · checked 1h ago

cloud-finops

https://mcp.optimnow.io

Registry code: 23a25736945a3f78

api record

Cloud FinOps knowledge by OptimNow. Two retrieval surfaces: REFERENCES (long-form provider/discipline files) and PLAYBOOKS (small named-pattern runbooks for specific waste patterns). REFERENCES: list_references() to discover, find_references(domain=, capability=, phase=, persona=, maturity=, persona_primary_only=) to narrow by FinOps Capability/Phase facets, get_reference(name=, section=) to fetch one body. Every listing entry carries approx_tokens. Read it before fetching: references run from about 3,000 to over 25,000 tokens. Above roughly 10,000, call get_reference(name=, section="<heading…

endpoint
https://mcp.optimnow.io/mcp
protocol
http-sse ·2025-06-18
authentication
none observed
public key
none — nobody has proven they own this listing · is it yours? claim it
karma
0 · newcomer
_ is it live, free and safe measured by this hub
Is cloud-finops live?
Yes — it answered the hub's last check (checked 1h ago). It answered 100% of checks over the last 30 days.
Is cloud-finops free to use?
Yes — the hub reached it with no key and no payment.
What tools does cloud-finops have?
6 tools: get_reference, list_playbooks, find_playbooks, get_playbook, find_references, list_references.
Is cloud-finops safe to connect?
The hub found no text in its card or tool descriptions aimed at the agent reading them. It measures what the server answers, not its code — grant it only the access its tools need.
reachable
live
uptime, 30 days
100%

90 days 100%· all time 100%

latency
227ms

last good check

priced tools
0

of 6 tools

_ answered our checks, 90 days 1 checks · signed record
  • unknown → live
_ usage and payments 30 days

Calls placed through this hub's router, from its own receipts. Every caller and every payer counts the same; the chain total is counted from three payers.

accounts
0

through this hub

calls served
0

successful

paid through this hub
0 USDC

what callers paid

_ what it can do 6 tools
2 open 4 never probed 2 of 6 classified

Price is per tool, not per server. An agent whose handshake is open can hold tools that demand a key or a payment, and one figure for the whole agent sends callers into a wall.

  • find_references open 1h ago

    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" - anything that maps to FinOps Framework facets (domain, capability, phase, persona, maturity) - and you want only the references that serve it, instead of scanning the full list. All filters are optional and combine with AND semantics. String matching is case-insensitive and exact (not substring). Examples: - ``find_references(domain="Optimize Usage & Cost")`` - ``find_references(phase="Optimize", persona="Engineering")`` - ``find_references(persona="Engineering", persona_primary_only=True)`` - ``find_references(capability="Rate Optimization")`` - ``find_references(maturity="Crawl")`` Args: domain: FinOps Framework domain (e.g. ``"Optimize Usage & Cost"``, ``"Quantify Business Value"``, ``"Manage the FinOps Practice"``). capability: FinOps capability (matches ``fcp_capability`` and ``fcp_capabilities_secondary``). phase: FinOps phase (``"Inform"``, ``"Optimize"``, ``"Operate"``). persona: Persona (matches ``fcp_personas_primary`` and ``fcp_personas_collaborating``). maturity: Entry maturity level (``"Crawl"``, ``"Walk"``, ``"Run"``). persona_primary_only: when True, ``persona`` matches only the primary list. Use it when the default match barely narrows the set - broad personas like Engineering collaborate on nearly every file, so filtering on collaboration is descriptive, not discriminating. ``persona="Engineering", persona_primary_only=True`` is the engineering reading list; the default is the everything-they-touch view. Returns ``{"filters": {...}, "references": [...], "total": N}``. A query that matches nothing also returns `hint` and `valid_values`, so a typo is distinguishable from a genuine gap in coverage.

    mcp-tool

    {
      "type": "object",
      "title": "find_referencesArguments",
      "properties": {
        "phase": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Phase",
          "default": null
        },
        "domain": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Domain",
          "default": null
        },
        "persona": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Persona",
          "default": null
        },
        "maturity": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Maturity",
          "default": null
        },
        "capability": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Capability",
          "default": null
        },
        "persona_primary_only": {
          "type": "boolean",
          "title": "Persona Primary Only",
          "default": false
        }
      }
    }
    arguments 71 lines
  • list_references open 1h ago

    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 fetch. When the question already names a FinOps domain, phase, persona or maturity, call ``find_references`` instead of scanning this full list. Returns a dict shaped ``{"references": [...], "total": N}`` where each entry includes ``name``, ``title``, a one-line ``description``, the discriminating FCP facets (``fcp_domain``, ``fcp_capability``, ``fcp_phases``, ``fcp_personas_primary``, ``fcp_maturity_entry``) and ``approx_tokens``. Read ``approx_tokens`` before fetching: the library runs from about 3,000 to over 25,000 tokens per file. Above roughly 10,000, prefer ``get_reference(name, section=...)`` and pull the part you need.

    mcp-tool

    {
      "type": "object",
      "title": "list_referencesArguments",
      "properties": {}
    }
    arguments 5 lines
  • get_reference unknown 1h ago

    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`` told you which one serves the question. Advisory questions (commitment sizing, chargeback design, allocation methodology) are served by the reference's decision rules and worked examples, which a summary does not carry. Pass ``section`` when the question is narrower than the file. The ``approx_tokens`` hint in the listing tells you when this matters: the provider pattern catalogues run past 25,000 tokens and are enumerated lists, so a question about S3 lifecycle wants one section of ``finops-aws-patterns``, not all of it. Omit ``section`` for the whole file when you need the cross-cutting reasoning. Args: name: Reference name as returned by ``list_references`` (e.g. ``"finops-aws"``, ``"finops-genai-capacity"``, ``"optimnow-methodology"``). section: Optional H2 or H3 heading to return on its own. Matched case-insensitively and partially against the headings, so a natural phrase works - ``"storage"``, ``"commitment decision tree"``. A heading's trailing count is ignored, so ``"storage optimization patterns"`` matches ``"Storage Optimization Patterns (28)"``. If it matches nothing you get the list of available headings back, not the whole file. Without ``section``, returns ``{"name": ..., "content": "...", "lines": N}`` where ``content`` is the file verbatim. With ``section``, returns ``{"name", "title", "section", "section_level", "partial": true, "content", "lines", "full_lines"}`` where ``content`` is that section prefixed by the reference's title, plus ``other_matching_sections`` when the phrase matched more than one heading. On a miss, returns ``{"error": ..., "suggestions": [...]}``. An unknown name gives up to three string-distance matches; an unmatched ``section`` gives ``available_sections`` - every heading in the file - so the retry is exact.

    mcp-tool

    {
      "type": "object",
      "title": "get_referenceArguments",
      "required": [
        "name"
      ],
      "properties": {
        "name": {
          "type": "string",
          "title": "Name"
        },
        "section": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Section",
          "default": null
        }
      }
    }
    arguments 25 lines
  • list_playbooks unknown never probed

    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 names a provider, waste category, or confidence tier, call ``find_playbooks`` instead. Each playbook is a small (~80-130 line) runbook scoped to one waste pattern (e.g. ``aws-zombie-nat-gateway``, ``azure-orphan-disks``). Returns ``{"playbooks": [...], "total": N}`` where each entry includes ``name``, ``title``, ``scope`` (aws/azure/gcp/cross-cloud), ``service``, ``waste_category``, ``confidence`` (obvious/likely/possible), and ``approx_tokens`` - the same size hint the reference listing carries, so a multi-playbook answer can be budgeted before fetching.

    mcp-tool

    {
      "type": "object",
      "title": "list_playbooksArguments",
      "properties": {}
    }
    arguments 5 lines
  • find_playbooks unknown never probed

    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 serves questions about the user's own resources. Use this for questions like "which VMs are running for nothing", "why is our NAT bill so high", "my NAT gateway processes 10TB to S3", "should I delete these old snapshots", "which of our RIs are about to expire", "what waste can we clean up safely without review" - anything that names a provider, a waste category, or how confident the detection needs to be before acting. Patterns covered include NAT gateways and VPC endpoints, expiring Savings Plans / RIs / reservations, snapshot sprawl, S3 lifecycle gaps, idle or stopped VMs, orphaned disks / public IPs / EBS volumes, GPU and SageMaker sizing, Kubernetes idle capacity, and schedule blindness. All filters are optional and combine with AND semantics. String matching is case-insensitive and exact. Examples: - ``find_playbooks(scope="aws")`` - all AWS-specific playbooks - ``find_playbooks(waste_category="idle")`` - every idle-resource pattern - ``find_playbooks(scope="cross-cloud", confidence="obvious")`` Args: scope: ``"aws"``, ``"azure"``, ``"gcp"``, or ``"cross-cloud"``. service: Provider service exact-match (e.g. ``"AWS NAT Gateway"``). waste_category: ``"orphaned"``, ``"idle"``, ``"overprovisioned"``, ``"commitment-mismatch"``, ``"schedule-blindness"``, ``"modernization"``, ``"ai-ml-inefficiency"``, or ``"egress"``. confidence: ``"obvious"`` (single signal is enough), ``"likely"`` (two signals required), or ``"possible"`` (needs human review). From the OptimNow three-tier confidence model in `finops-waste-detection-playbooks`. Returns ``{"filters": {...}, "playbooks": [...], "total": N}``. A query that matches nothing also returns `hint` and `valid_values`, so a typo is distinguishable from a genuine gap in coverage.

    mcp-tool

    {
      "type": "object",
      "title": "find_playbooksArguments",
      "properties": {
        "scope": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Scope",
          "default": null
        },
        "service": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Service",
          "default": null
        },
        "confidence": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Confidence",
          "default": null
        },
        "waste_category": {
          "anyOf": [
            {
              "type": "string"
            },
            {
              "type": "null"
            }
          ],
          "title": "Waste Category",
          "default": null
        }
      }
    }
    arguments 54 lines
  • get_playbook unknown never probed

    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 SageMaker endpoint, ...). It also serves questions about the user's own resources ("which of my X..."): the runbook's detection query is written to be run in the user's account, so the answer does not depend on access to that account. Args: name: Playbook slug as returned by ``list_playbooks`` (e.g. ``"aws-zombie-nat-gateway"``, ``"azure-orphan-disks"``, ``"cross-cloud-untagged-spend-drift"``). Returns ``{"name": ..., "title": ..., "content": "...", "lines": N}``. On miss, returns ``{"error": ..., "suggestions": [...]}`` with up to three string-distance matches so the caller can self-correct. A host with MCP Apps (SEP-1865) support may render this result via the linked ``ui://cloud-finops/playbook-viewer`` resource instead of showing the raw markdown.

    mcp-tool

    {
      "type": "object",
      "title": "get_playbookArguments",
      "required": [
        "name"
      ],
      "properties": {
        "name": {
          "type": "string",
          "title": "Name"
        }
      }
    }
    arguments 13 lines
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