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Finops Framework MCP

by aaronmsotoversion 0.2.0i★ –iRuns on your computer
Registry nameio.github.aaronmsoto/finops-framework-mcp

Install

Overview

Description from the maker (original English)

Unofficial MCP server for the FinOps Framework: phases, domains, capabilities, maturity, KPIs.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: FINOPS_MCP_DATA

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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": {
    "finops-framework": {
      "command": "npx",
      "args": [
        "-y",
        "finops-framework-mcp"
      ],
      "env": {
        "FINOPS_MCP_DATA": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add finops-framework --env FINOPS_MCP_DATA=your-value -- npx -y finops-framework-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "finops-framework": {
      "command": "npx",
      "args": [
        "-y",
        "finops-framework-mcp"
      ],
      "env": {
        "FINOPS_MCP_DATA": "your-value"
      }
    }
  }
}

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.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "finops-framework": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "finops-framework-mcp"
      ],
      "env": {
        "FINOPS_MCP_DATA": "your-value"
      }
    }
  }
}

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.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • FINOPS_MCP_DATA env
    Override the bundled data artifact directory (defaults to the packaged data/framework).

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

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

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account aaronmsoto, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32572 servers in this category
  • Published to the registry more recently than 68% of the other 32572 servers in this category
  • Basic checks equal to or better than 100% of the other 32572 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Finops Framework MCP safe?

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.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

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).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.0) reached the registry 17 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, AvaHR

Alternatives

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Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated yesterday
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AvaHR

by avahr.com

Read hiring data and create inactive assessment and questionnaire drafts for human review.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

finops-framework-mcp

Three unofficial MCP servers that give AI assistants a structured, sourced interface to published FinOps and AI-cost guidance, so an assistant answers with the publishers' actual text and formulas instead of improvising:

ServerCoversSource
finops-framework-mcpThe FinOps Framework: capabilities, Crawl/Walk/Run maturity, KPIs, personasfinops.org/framework
finops-focus-mcpThe FOCUS billing-data specification, pinned per version (1.0, 1.2)focus.finops.org
tokenomics-overview-mcpAI tokenomics: the Seven-Layer Stack, Big-T notation, prompt-cache metrics, consumption levers incl. model routing, FOCUS 1.5 AI costtokeneconomics.com

All three are read-only (an agent can read guidance, never change your practice or data) and offline once installed (no network access at runtime, no telemetry). Use any one on its own; together they cover what good looks like, which billing columns prove it, and what drives AI token cost.

Start here: the usage guide

[aaronmsoto.github.io/finops-framework-mcp](https://aaronmsoto.github.io/finops-framework-mcp/) is a free, no-install walkthrough written for FinOps practitioners as much as engineers. It explains what each server does, connects them to Claude in a couple of minutes, and works through five examples, from a showback report to whether prompt caching is paying off. Every number and quote in it comes from a real run of these servers. See Documentation for the page list.

Why this exists

Ask an AI assistant "how mature is our Allocation practice?", "which FOCUS columns feed Effective Savings Rate?" or "is our prompt caching paying off?" without these servers, and it will happily improvise a plausible answer. With them, every response is the publisher's own text and formulas, structured for an assistant to read, with the source URL and license attached.

Anything a server had to work out itself is labeled, never passed off as published guidance:

  • The FOCUS server's KPI-to-column mapping, computed KPI values and cross-version diff are marked UNOFFICIAL (official: false).
  • The tokenomics server states each source's publication status on every answer, because most Tokenomics Foundation guidance is a working draft or release candidate. Its curated crosswalk is unofficial and only appears with FINOPS_MCP_EXPERIMENTAL=1.
  • The framework server is official-only out of the box: no invented relationships between capabilities, no maturity levels beyond the Foundation's Crawl/Walk/Run.

Quickstart

All three are on npm, so there is nothing to clone or build. Each package ships its own data and runs offline. Node >= 22 is the only requirement.

npx -y finops-framework-mcp

npx -y finops-focus-mcp npx -y tokenomics-overview-mcp

(-y skips npx's first-run install prompt, which can hang non-interactive MCP clients. Pin a version with, for example, npx -y finops-focus-mcp@0.2.)

Claude Code:

claude mcp add finops-framework -- npx -y finops-framework-mcp

claude mcp add focus-spec -- npx -y finops-focus-mcp claude mcp add tokenomics-overview -- npx -y tokenomics-overview-mcp

Claude Desktop (claude_desktop_config.json), or a project-scoped .mcp.json, or any stdio MCP client:

{

"mcpServers": { "finops-framework": { "command": "npx", "args": ["-y", "finops-framework-mcp"] }, "focus-spec": { "command": "npx", "args": ["-y", "finops-focus-mcp"] }, "tokenomics-overview": { "command": "npx", "args": ["-y", "tokenomics-overview-mcp"] } } }

Environment variables (all optional):

VariableServerEffect
FINOPS_MCP_DATAframeworkUse a locally refreshed artifact instead of the packaged data/framework
FOCUS_MCP_DATAFOCUSSame, for data/focus
TOKENOMICS_MCP_DATAtokenomicsSame, for data/tokenomics
FINOPS_MCP_EXPERIMENTAL=1framework, tokenomicsTurn on clearly labeled unofficial extras: the framework's parsed maturity get_actions, the tokenomics crosswalk

Each server also accepts the data directory as its first CLI argument, and answers --version with its package version plus its data version (FOCUS: the spec versions it serves).

How to use them

Start a session with each server's entry point, then follow its suggestions:

ServerStart withThen
frameworkget_framework_info {}search_framework, list_capabilities, get_capability (with include to control size), get_kpis, assess_maturity_path
FOCUSlist_versions {}search_focus, get_column, get_requirements, compare_versions, get_kpi_mapping, calculate_kpi
tokenomicsget_tokenomics_info {}list_layers, get_bigt_notation, list_levers, get_metric, calculate_cache_metrics, get_crosslinks

Questions each one answers well:

  • Framework: "What does Walk-level Forecasting require?", "Which KPIs does the Foundation feature for Rate Optimization?", "Who does what in Anomaly Management?"
  • FOCUS: "What does BilledCost mean in 1.2, and what changed since 1.0?", "Which columns do I need to compute Effective Savings Rate?"
  • Tokenomics: "Which layer owns model routing and AI gateways?", "How does this agent's token use scale with autonomy?", "Our cache read, write and uncached input tokens were X, Y, Z: is caching saving money?"

Using them together. The servers ship separately and never call each other. Instead, answers hand off by URI: each of the tokenomics server's 35 get_crosslinks links is backed by a verbatim quote from the Tokenomics Foundation page, and carries a finops://framework/… or focus://spec/… URI for the agent to read with the other two servers. FOCUS 1.5 working-draft names, which no ratified release contains yet, come back with no URI. The prompt-caching example walks one question through all three.

Server surfaces
  • finops-framework-mcp: 11 tools — get_framework_info (entry point), search_framework, list_capabilities, get_capability, get_maturity_assessment, get_kpis, assess_maturity_path, map_personas, get_entity, get_maturity_model, get_changelog — plus finops://framework/… resources and 4 prompts (explain-framework, assess-capability-maturity, plan-maturity-roadmap, map-personas-to-capabilities). Data: 6 Principles, 3 Phases, 4 Domains, 22 Capabilities, 11 Personas, 5 Technology Categories, the Scopes concept, and an 88-entry KPI library.
  • finops-focus-mcp: 9 tools for column and attribute lookup, normative requirements, search, the 1.0 → 1.2 diff, and unofficial KPI-to-column mappings with sample-data KPI calculation, plus focus://spec/… resources and 3 prompts. See packages/finops-focus-mcp.
  • tokenomics-overview-mcp: 20 tools across documents, the Seven-Layer Stack, Big-T notation, levers, metrics (with a cache-metrics calculator), personas, value classification, the FOCUS 1.5 AI-cost capabilities and cross-links, plus tokenomics://overview/… resources and 3 prompts (optimize_consumption, assess_prompt_caching, bigt_review). Data: 14 source documents, 7 layers, 6 Big-T classes, 32 levers, 7 metrics, 12 personas, 35 stated cross-links. See packages/tokenomics-overview-mcp.

The full prompts, resources and tools of all three servers (names, arguments, URIs, defaults and limits) are generated from live MCP output in docs/mcp-surface.md.

Remote option: the Cloudflare Worker

All three servers can also run over Streamable HTTP from one bundled Cloudflare Worker (src/workers/, endpoints /mcp/framework, /mcp/focus and /mcp/tokenomics; see docs/deploy-worker.md). Any MCP client that speaks Streamable HTTP can connect to a deployed Worker, for example:

claude mcp add --transport http tokenomics-overview "$WORKER_URL/mcp/tokenomics"

The Worker is stateless and serves each server's default surface (no experimental tools). demo/ is a static browser page with two walkthroughs through it: "Is prompt caching paying off?" (all three servers, on your own token counts) and Rate Optimization (framework and FOCUS).

How it's built

Every server is the same three decoupled parts, so a content refresh never needs a code change:

crawler ──▶ data artifact ──▶ MCP server (stdio)

src/crawlers/ data/ / src/servers/

for in framework, focus and tokenomics. The framework and tokenomics crawlers go fetch → parse → compose → derive → validate → emit: content/markdown/ is the canonical intermediate, composed from parsed HTML, and every JSON file is regenerated from it by an offline derive step, so a schema or JSON-only fix never needs a re-crawl. Their artifacts carry JSON Schemas and a sha256 manifest, and each server validates its artifact at startup and refuses to start on a bad one. The FOCUS crawler instead ingests each pinned spec release by git tag into data/focus/ /, with the derived diff and KPI mapping under data/focus/derived/.

The framework server's early capability relationship graph (get_prerequisites/get_related) was built, evaluated and deleted because its edges didn't clear the accuracy bar; see .agents/specs/v1-official-only.md.

Refreshing the data

npm run build

npm run refresh # framework: crawl → artifact + diff report node dist/crawlers/focus/cli.js # FOCUS: ingest the pinned spec tags (1.0, 1.2) node dist/crawlers/tokenomics/cli.js refresh # tokenomics: Tokenomics Foundation pages node dist/crawlers/framework/cli.js derive # framework: offline markdown → JSON, byte-identical node dist/crawlers/tokenomics/cli.js derive # tokenomics: same, for data/tokenomics

Crawls are polite, cached and robots-honoring. No upstream changes produce a byte-identical artifact and no version bump; content changes produce a changelog entry and a semver bump of the data version. The tokenomics refresh also lists pages it found but doesn't ingest (for example working-group drafts) under unregistered in its manifest. A scheduled refresh workflow is provided at docs/proposed/refresh-data.yml; .github/workflows/ is a protected path here, so the owner installs it:

git mv docs/proposed/refresh-data.yml .github/workflows/refresh-data.yml

Data versioning policy

Consumers pin a data version by pinning a package version or a git ref of this repo. Each manifest.json carries data_version, schema_version, crawled_at, per-file sha256 and entity counts; derived/changelog.json records what changed between versions (served by the framework server as get_changelog). Schema-breaking chang

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