Modelmeter
The changelog of record for the AI stack: sunset checks, deprecations, pricing, and model events.
Installation
Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).
claude mcp add --transport http modelmeter 'https://modelmeter.xyz/mcp'
{
"mcpServers": {
"modelmeter": {
"type": "http",
"url": "https://modelmeter.xyz/mcp"
}
}
}
Documentation
Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent 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 modelsGET /models— current model catalog, with filtersGET /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 billGET /deprecations— per-model retirement rows: which model dies when, with runway and migration targetGET /feed.xml/GET /feed.json— RSS 2.0 / JSON Feed 1.1 of breaking and action-required eventsGET /events— the changelog of record: deprecations, price changes, launches and surrounding market events, each withseverity(breaking|action_required|informational),announced_at/effective_atdates, sources with quotes, and verificationstatus. Filters:provider,type,model,severity,since,until,statusGET /history— historical pricing time-series per model, with filtersGET /pricing.json— raw pricing snapshotGET /events.json— raw events snapshotGET /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 warn
The 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/mcp
Tools: check_model_dependencies, list_deprecations, estimate_cost, get_model, list_models, get_price_history, list_events. Start with list_models to discover ids, then get_model or estimate_cost. The MCP tools return the same data as the REST endpoints above — use whichever your runtime prefers.
Datasets
pricing/— current and historical model pricing across providersevents/— the events record (schema 2.0.0): deprecations, price changes, releases, and market events with primary-source citations, verbatim quotes, and verification status
Each entry carries a last_verified date. Daily snapshots in pricing/snapshots/ accumulate the historical record. Wrong pricing is the existential risk — the schema requires explicit human verification before an entry is served.
Contributing
Found a price change? Open a PR updating pricing/current.json with the new value, an updated last_verified date, and the source URL.
Spotted a meaningful AI market event? Add an entry to events/current.json with primary-source citations and verified: true.
Automation opens issues when provider pricing pages change. Pick one up if you want to help.
License
MIT — see LICENSE.
Questions fréquentes
Qu'est-ce que Modelmeter ?
The changelog of record for the AI stack: sunset checks, deprecations, pricing, and model events.
Comment installer Modelmeter ?
Il fonctionne comme serveur distant. Dans Claude Code : claude mcp add --transport http modelmeter 'https://modelmeter.xyz/mcp'. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.
Faut-il une clé API pour Modelmeter ?
Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.
Modelmeter est-il open source ?
Oui. Son code est sur GitHub sous licence MIT.
Qui maintient Modelmeter ?
Il est publié par modelmeters. AI.tn le référence sans le maintenir ni le recommander.
Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.