stalemodel
Provides Gemini model ID validation, deprecation checks, newer-model suggestions, and current pricing and context lookup for Google Gemini models.
Provides tools for checking OpenAI GPT model IDs, identifying deprecated or unknown IDs, suggesting newer models, and looking up current pricing and context limits.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
stalemodel: find deprecated AI model names in your code
Catch outdated OpenAI, Claude and Gemini model IDs before your coding agent ships them, and look up current LLM prices and context limits.
Coding agents write model IDs from old training data, so new code often calls models that are deprecated or gone, and fails with errors like "model not found". stalemodel checks IDs against a live catalog, suggests the newest model in the same family, and gives agents current LLM pricing and limits. It's an MCP server and a CLI. It needs no API key or account, sends no code anywhere, and falls back to a bundled snapshot when offline.
It covers Anthropic Claude, OpenAI GPT, Google Gemini, xAI Grok, DeepSeek and Mistral.
What you can ask your agent
"Which Claude model ID should I use, and what does it cost?"
"Why do I get 'model not found' for claude-3-5-sonnet-20241022?"
"Check this repo for deprecated model names."
"What's the cheapest current model with tool calling and a 1M context window?"
Related MCP server: LLMIntel Model Lifecycle
Install
As a Claude Code plugin, which adds the MCP server and a skill that tells Claude when to use it:
claude plugin marketplace add GillMacedo/stalemodel
claude plugin install stalemodel@stalemodel-marketplaceFor other MCP clients, run it from npm. You need Node 22.19 or newer. It's also in the official MCP Registry as io.github.GillMacedo/stalemodel.
{
"mcpServers": {
"stalemodel": {
"command": "npx",
"args": ["-y", "stalemodel", "serve"]
}
}
}Usage
Without installing anything, run npx stalemodel scan .. The examples below run from a clone of this repo.
Scan a project. Only quoted strings count, and scan exits 1 on findings, so it can run in CI.
$ node plugin/dist/stalemodel.js scan examples
examples/app.py:2 claude-3-5-sonnet-20241022 not in catalog try claude-sonnet-5-5
examples/app.py:3 gpt-3.5-turbo deprecated try gpt-5.5
examples/app.py:4 gemini-1.5-pro not in catalog try gemini-2.5-pro
3 findings in 1 filesCheck an ID.
$ node plugin/dist/stalemodel.js check gpt-4o claude-opus-5-5
gpt-4o current try gpt-5.5
claude-opus-5-5 currentFind current models, newest first, with prices per million tokens.
$ node plugin/dist/stalemodel.js find --provider anthropic --limit 2
claude-haiku-5-5 anthropic 2026-10-07 $0.1/$0.5 per MTok 1000000 context
claude-sonnet-5-5 anthropic 2026-09-28 $2/$10 per MTok 1000000 contextAdd --json for machine-readable output, or --offline to use only the bundled snapshot. These examples use the snapshot from 2026-10-31, so live results will change.
MCP tools
Tool | What it does |
| Says whether IDs are current, deprecated or unknown, and suggests a newer model |
| Lists models by provider, name, price, context size or tool support |
| Finds outdated IDs in a file or folder, returning locations only |
All three are read-only.
Limits
Data comes from models.dev, so it can lag behind providers or contain errors.
"Not in catalog" can also mean a new, private or misspelled model.
tryis a suggestion based on family and release date. Check price and behavior before switching.scanonly sees quoted IDs, so it misses IDs built at runtime. It also doesn't flag baregpt-4o-style IDs that are old but still current.
FAQ
How do I find deprecated LLM models in my code? Run npx stalemodel scan .. It exits 1 on findings, so it also works as a CI check.
Where does the pricing data come from? From models.dev, fetched live, with a snapshot bundled for offline use.
Does it work outside Claude Code? It's a standard MCP server, so it should work in any MCP client. So far it has only been tested in Claude Code.
Contributing
Contributions are welcome, from people and from people working with AI agents. See CONTRIBUTING.md. Good first issues:
Add a GitHub Action that runs
scanon pull requestsAdd an option to flag current models that have a newer version
Support Bedrock and Vertex model ID formats
Add a
--fixoption that shows a diff of suggested replacementsAdd a plugin icon
How pull requests work
Open a PR. Fork the repo, work on a branch, and keep it to one change. Write a title that says what changes for users, because it becomes the changelog line:
feat:goes under Added andfix:under Fixed.Automatic check. Code changes need tests, and
make testmust pass. Changes over 30 lines need a linked open issue (Closes #<number>), and a PR can have at most 800 changed lines. If something is missing, a comment tells you what to fix.Review. Claude reviews each PR automatically. Code PRs also get a security review and are tested in a sandbox. The review then merges the PR or asks for changes. PRs that change CI, agent settings, npm or Python dependencies, vendored code or build files can't be merged this way, and a comment says so. The same goes for anything the security review doesn't clear.
Release. A merge that changes what users install becomes a new version within about two hours, with a GitHub Release and, if the project has one, its npm package. Docs and CI changes wait for the next release.
AI disclosure
This project was largely generated with Claude Code and reviewed by its maintainer.
About me
I'm Giulliano Macedo, and I build developer tools at GoTech Solutions. Follow along or get in touch:
GitHub: GillMacedo
LinkedIn: giulliano
X: @giumacedo
If stalemodel helped you, a star helps others find it.
MIT licensed. Model data from models.dev (MIT).
Built by Giulliano Macedo, GoTech Solutions · LinkedIn · X
This server cannot be deployed
Maintenance
Related MCP Connectors
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Find retiring AI models and outdated API SDKs in your code, with dates, replacements and guides.
Check whether an LLM model id is deprecated, retiring, or retired, and what to migrate to.
Live registry of AI model specs, context windows, and per-token pricing.
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