Modelmeter MCP server
online · 100% uptimexyz.modelmeter/modelmeter·v1.0.0·1 starsThe changelog of record for the AI stack: sunset checks, deprecations, pricing, and model events.
1 stars
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Modelmeter tools (7)
write = sends, deletes, buys or postscheck_model_dependenciesFreeIs my stack okay? Check a list of model ids against the record: scheduled retirements with days-remaining countdowns and migration targets, past retirements, and other breaking/action-required changes. Id matching tolerates dots vs dashes, dated snapshot suffixes, and bare or provider-prefixed forms. Call this at startup or in CI with the models you depend on.
estimate_costFreeEstimate the USD cost of an LLM API call for a given model and token counts. Returns input/output/total cost, plus reseller markup vs. the upstream model when applicable.
get_modelFreeUnified card for one model in a single call: normalized pricing, capabilities (context window, vision, reasoning, tags), availability, reseller markup vs. upstream, and a price-history summary (launch vs. current price, percent change, last change date, all-time low/high).
get_price_historyFreeHistorical pricing time-series for a model or provider. Each point is a dated snapshot of the per-Mtok rates.
list_deprecationsFreePer-model retirement rows from the record: which model dies when, with runway and migration target. Default shows scheduled (upcoming) retirements sorted by shutdown date.
list_eventsFreeThe changelog of record for the model layer: deprecations, price changes, launches, and the market events around them. Filter by severity to find what demands action: 'breaking' (model going away, ID changing), 'action_required' (price/rate-limit/context changes), 'informational' (releases, funding).
list_modelsFreeList available models with their current pricing. Optionally filter by provider.
Public scan report
scanner v0.1.9 · 2026-09-26 · same rubric, same numbers if you re-run it
- –Code scanremote-only server, no package to scann/a
- Live reliabilityremote reachable in 425ms20/20
- Tool poisoning7 tool descriptions checked15/15
- Auth qualityopen endpoint, read-only tools10/15
- Maintenancelast push 43 days ago12/15
- Maintainer identitynamespace and repository owner differ; website matches verified namespace5/10
How Modelmeter compares
Against every graded AI and agents MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 83/100
- higher than 68% of 4,460 AI and agents servers
- Tools
- 7
- the typical AI and agents server has 6
- Tools that change things
- 0%
- typical: 0%. Fewer write tools means less an agent can break
- Uptime
- 100%
- of our recent checks; the typical remote AI and agents server answers 100%
- Response time
- 178 ms
- faster than 71% of 2,331 AI and agents servers
- GitHub stars
- 1
- more than 50% of 2,711 AI and agents servers
What its tools let an agent do: 7 read
Install Modelmeter in Claude Code, Cursor or VS Code
claude mcp add --transport http modelmeter https://modelmeter.xyz/mcp
What the publisher says
From the Modelmeter repository's README, as published. We do not edit it. Read it on GitHub
Modelmeter
The changelog of record for the AI stack. Live at modelmeter.xyz.
What this is
A machine-readable, source-verified record of everything that changes in the model layer: deprecations with sunset dates and migration targets, silent model swaps behind stable IDs, price changes, releases — plus three years of pricing history and cost tooling. Every event carries its sources with verbatim quotes (most with archive snapshots), a verification status (unverified → human-reviewed verified), and corrections are never silent — a correction event points at what it supersedes.
Built primarily for AI agents to call programmatically, secondarily for humans through a dashboard. Reach it three ways: plain GET URLs returning JSON, a remote MCP server any tool-calling agent can connect to, and a visual dashboard built on the same endpoints. The wedge: clean URLs, stable JSON contracts, an OpenAPI spec, and an llms.txt discoverability file. Most sites in this space are JS-heavy SPAs that agents can't use; Modelmeter is built the other way around.
Endpoints
- GET /estimate?model=X&input=N&output=M — token cost for a hypothetical call, including upstream-markup comparison for reseller models
- GET /models — current model catalog, with filters
- GET /model?id=X — unified card for one model: normalized pricing, capabilities (context window, vision, reasoning, tags), availability, reseller markup, and a price-history summary (launch vs. current price, % change, all-time low/high)
- GET /check?models=gpt-4o,claude-sonnet-4-6 — is my stack okay? Verdict per model: scheduled retirements with days-remaining and migration targets, past retirements, breaking changes, or a clean bill
- GET /deprecations — per-model retirement rows: which model dies when, with runway and migration target
- GET /feed.xml / GET /feed.json — RSS 2.0 / JSON Feed 1.1 of breaking and action-required events
- GET /events — the changelog of record: deprecations, price changes, launches and surrounding market events, each with severity (breaking | actionrequired | informational), announcedat/effective_at dates, sources with quotes, and verification status. Filters: provider, type, model, severity, since, until, status
- GET /history — historical pricing time-series per model, with filters
- GET /pricing.json — raw pricing snapshot
- GET /events.json — raw events snapshot
- GET /history.json — raw historical time-series
See public/openapi.yaml for the full spec.
GitHub Action
Fail CI when a model your repo depends on is deprecated, sunsetting, or already retired:
- uses: modelmeters/modelmeter/actions/check@main
# with:
# models: "gpt-4o, claude-sonnet-4-6" # optional — otherwise the repo is scanned for known model ids
# fail-on: breaking # breaking (default) | retired | none
# warn-days: "120" # sunsets within N days fail; beyond N warnThe action scans your repo for known model ids (catalog + every model named in a deprecation event, dashed and dotted spellings), calls /check, annotates the exact file:line of each affected model, writes a job-summary table with migration targets, and exits nonzero per your fail-on policy.
MCP server
Modelmeter is also a remote MCP server, so any tool-calling agent (Claude, Hermes, …) can call it natively over the Streamable HTTP transport — no auth, no install:
https://modelmeter.xyz/mcpTools: checkmodeldependencies, listdeprecations, estimatecost, getmodel, listmodels, getpricehistory, listevents. Start with listmodels to discover ids, then getmodel or estimatecost. The MCP tools return the same data as the REST endpoints above — use whichever your runtime prefers.
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Modelmeter: common questions
- Is Modelmeter MCP server safe?
- Mostly: it is graded B (83/100). Read the Modelmeter safety report
- How do I install Modelmeter?
- It runs remotely at modelmeter.xyz. Add it to Claude Code, Cursor, VS Code or Claude Desktop with the snippets above, or call it through the mcp.market gateway without installing anything.
- Does Modelmeter need an API key?
- Not as far as the registry entry and our scan can tell: no credentials are declared or required.
- Is Modelmeter maintained?
- The last commit was 82 days ago (2026-08-14). The latest release is v1.0.0.
- Is Modelmeter up?
- 100% of our last 28 checks got an answer. We check remote servers about four times a day.
- What can I use instead of Modelmeter?
- Servers from other publishers that do the same job: Mockserver MCP server, CHAP Coordinator MCP server and Kiln MCP server.
- How does Modelmeter compare with other AI and agents MCP servers?
- safety score 83/100 (higher than 68% of 4,460 AI and agents servers); tools 7 (the typical AI and agents server has 6); tools that change things 0% (typical: 0%. Fewer write tools means less an agent can break). Full comparison.
Alternatives to Modelmeter
Same job from other publishers: the closest match first, then the best rated.
- MockserverMock, record/replay, verify and chaos-test any HTTP, REST, gRPC or LLM dependency over MCP.not reviewedEstablishedA
- CHAP CoordinatorAuditable records of human decisions over AI agent work. Approvals, edits, overrides, escalations.not reviewedEstablishedA
- KilnSpawn an object into existence: describe it, and your agent designs it, checks it, and 3D prints it.not reviewedEstablishedB
- three.ws ProvenanceAppend-only, signed, on-chain-verifiable agent action log — record and audit what agents did.not reviewedEstablishedB
- Vibe CheckMetacognitive AI agent oversight: adaptive CPI interrupts for alignment, reflection and safetynot reviewedEstablishedB