cloud-finops-mcp

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Browse the FinOps knowledge library

list_references

Read-onlyIdempotent

Lists available FinOps guidance across billing, commitments, allocation, AI costs, and cloud providers, helping users discover coverage before fetching a specific reference.

Instructions

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 2,000
to about 15,000 tokens per file. Above roughly 10,000, prefer
``get_reference(name, section=...)`` and pull the part you need.

Input Schema

Name	Required	Description	Default
No arguments

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 17, 2026

TDQS

A4.8/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely new operational context: the token size range per file (~2,000–15,000), the ~10,000 threshold where fetching becomes expensive, and the section-scoped workaround. That is exactly the cost/behavior information an agent cannot get from structured fields.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose and the sibling routing are front-loaded in the first two paragraphs, which is the right ordering. The third paragraph spells out the response dict field-by-field even though an output schema already exists, which is slightly redundant bulk, though the approx_tokens advice that follows does earn its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-argument discovery tool this leaves nothing an agent needs unanswered: scope, alternative tool, response shape, per-item facets, and the token-cost decision rule. The output schema exists, so the extra return-value prose is redundant rather than required, but completeness is not lacking.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The description does usefully explain which fields appear in each returned entry, but that is return-value detail rather than parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Opens with a specific verb+resource ('See what FinOps guidance is available') and enumerates the concrete domains and providers covered, so an agent knows exactly what is in the library. It is clearly distinguishable from find_references, get_reference, and the playbook siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

States the intended use ('discover what the library covers before deciding what to fetch') and an explicit exclusion with the alternative: when a FinOps domain, phase, persona or maturity is already named, call find_references instead. It also routes oversized files to get_reference(name, section=...).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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