LLMIntel Model Lifecycle
Overview
Description from the maker (original English)
Check whether an LLM model id is deprecated, retiring, or retired, and what to migrate to.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews from signed-in users. The average shows once there are reviews
- Our basic checksi5 of 5 passedChecked from public information; code not scanned yet
- UsageiEarly↓ 140/wk · ★ 1
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: Computer or cloud
- Transport: stdio, Streamable HTTP
- Category: Search & AI memory
- You need to fill in: LLMINTEL_API_KEY
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 5 of 5 passed
- Runs on the maker’s server: what you ask it goes through their server.
- Can do 5 things (tools) check_model, list_retiring_models, suggest_replacement, search_models …
- You fill in yourself:
LLMINTEL_API_KEY,LLMINTEL_BASE_URL
Values marked secret are keys to your account. Never share them or paste them into a chat.
You need
- Runs in the cloudNothing to install; it connects over the internet
- 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 …”.
Works in Claude on the web, desktop and mobile:
- Open Settings → Connectors
- Press Add custom connector
- Paste the address below and press Add
- If it asks you to sign in, sign in with the maker
https://llmintel.ai/v1/mcpOr run it on your computer
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"model-lifecycle": {
"command": "npx",
"args": [
"-y",
"@llmintel/mcp"
],
"env": {
"LLMINTEL_API_KEY": "your-value",
"LLMINTEL_BASE_URL": "your-value"
}
}
}
}Run this in your terminal
claude mcp add --transport http model-lifecycle https://llmintel.ai/v1/mcpOr run it on your computer
claude mcp add model-lifecycle --env LLMINTEL_API_KEY=your-value --env LLMINTEL_BASE_URL=your-value -- npx -y @llmintel/mcpFill in the empty values before running it.
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"model-lifecycle": {
"url": "https://llmintel.ai/v1/mcp"
}
}
}Or run it on your computer
Or copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"model-lifecycle": {
"command": "npx",
"args": [
"-y",
"@llmintel/mcp"
],
"env": {
"LLMINTEL_API_KEY": "your-value",
"LLMINTEL_BASE_URL": "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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"model-lifecycle": {
"type": "http",
"url": "https://llmintel.ai/v1/mcp"
}
}
}Or run it on your computer
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"model-lifecycle": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@llmintel/mcp"
],
"env": {
"LLMINTEL_API_KEY": "your-value",
"LLMINTEL_BASE_URL": "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.
ChatGPT connects only to servers on the internet:
- Works with ChatGPT Business, Enterprise and Edu on the web; a workspace owner or admin adds it
- Go to Plugins, press + and choose Add custom MCP server
- Give it a name, paste the address below and set up sign-in as the maker says
- Read the warning, tick to accept, then choose Create as a plugin
https://llmintel.ai/v1/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
Values you fill in
- Optional. The catalog is public and needs no key; supplying one only raises the rate-limit budget.
LLMINTEL_BASE_URLenvOptional. Override the catalog origin (defaults to https://llmintel.ai). Useful for self-hosted or staging deployments.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Which apps can use it
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Connect over the internet in
ClaudeChatGPTGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatOpen WebUIRaycast
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Related guides
What it can do
Tool names and descriptions exactly as the server reported them on Nov 10, 2026. The maker wrote them, not us; we show them as plain text.
check_modelCheck whether an LLM model id is safe to use, deprecated, or retired, and what to migrate to. Accepts the exact string used in code (e.g. 'gpt-4o', 'claude-sonnet-4-5-20250929', 'anthropic/claude-opus-4-1'). Call this before writing or changing any hardcoded model id.
list_retiring_modelsList tracked models scheduled to retire within a time window, soonest first. Use this to audit a codebase or plan migration work.
suggest_replacementGiven a deprecated or retiring model, return the provider's recommended replacement(s) and, when none is published, active models from the same provider to consider.
search_modelsList tracked models, optionally filtered by provider and lifecycle state. Use this to discover what is currently available from a provider.
recent_lifecycle_changesLifecycle state changes across all tracked providers, newest first. Use this to answer 'what model deprecations happened recently?'.
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 11, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified against the domain llmintel.ai (the registry checks domain ownership)
- ✓ Pass
Still maintained
Code last changed 22 days ago
- ✓ Pass
Has a licence
Uses MIT
- ✓ Pass
Endpoint responds
Responded in 224 ms (HTTP 200)
- – Not applicable
Sign-in with OAuth
No sign-in needed
- ✓ Pass
No hidden instructions in tool descriptions
Read 5 tool descriptions and found no hidden instructions to the AI
Discussion
Ask, share a tip or report that it does not work. Sorted by what people marked helpful.
No posts yet. Be the first to ask or share.
Posts here are written by users, not the PopNx team.
User reviews
No reviews yet
Compared with others in Search & AI memoryi
- More stars than 74% of the other 5868 servers in this category
- Published to the registry more recently than 25% of the other 5868 servers in this category
- Basic checks equal to or better than 100% of the other 5868 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 LLMIntel Model Lifecycle safe?
It passed 5 of 5 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?
You need to fill in: LLMINTEL_API_KEY
Does it run on my computer or in the cloud?
Either way works: install it on your computer or connect to the cloud version.
Is it still maintained?
The GitHub repo last changed 22 days ago, and the latest version (0.2.0) reached the registry 4 months ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT Business and above.
What can I use instead?
In the same category: Ruflo, Context7, Metabase
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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.
@llmintel/mcp
An MCP server that tells your coding agent whether a model id is safe to use.
LLMs are trained on a snapshot of the world and will confidently write gpt-4-32k into your code long after it stops answering. This server gives the agent a live lookup for whether a model is deprecated and when it stops working. It returns the replacement too. Answers are normalized across OpenAI, Anthropic, Azure AI Foundry, AWS Bedrock, Google, and Cohere, and parsed from each provider's own deprecation pages.
No API key, no signup. The catalog is public.
Install
Add it to any MCP host. The package runs straight from npm via npx.
Cursor
In .cursor/mcp.json:
{
"mcpServers": { "llmintel": { "command": "npx", "args": ["-y", "@llmintel/mcp"] } } }
Claude Code
claude mcp add llmintel -- npx -y @llmintel/mcp
Claude Desktop
Same shape as the Cursor block above, in claude_desktop_config.json.
Hosted endpoint (no install)
The same five tools are served over Streamable HTTP at https://llmintel.ai/v1/mcp. Hosts that take a URL need no Node and no package:
{
"mcpServers": { "llmintel": { "url": "https://llmintel.ai/v1/mcp" } } }
The endpoint is stateless and read-only. It answers from the same catalog the npm package queries.
Tools
| Tool | Returns |
|---|---|
check_model | Whether one model id is safe to use: lifecycle state, the retirement deadline in days, the replacement, and the source link. |
list_retiring_models | What breaks in the next 180 days (default; configurable up to 1095). Past-due models are listed first, then upcoming ones soonest-first. |
suggest_replacement | The provider's own recommendation for what to move to. Falls back to same-provider active models when none was published. |
search_models | Catalog search filtered by provider and lifecycle state. |
recent_lifecycle_changes | The change feed across all providers, for questions like "what was deprecated this month". |
Example
You: Before we ship this, check the model ids in
src/agents/.
The agent calls check_model for each one and gets back:
DO NOT USE — this model is retired; API calls to it fail.
"claude-sonnet-4-20250514" resolves to the tracked model anthropic/claude-sonnet-4-20250514. Model: claude-sonnet-4-20250514 (anthropic/claude-sonnet-4-20250514) Provider: anthropic Lifecycle state: retired — retired; calls fail Deprecated: 2026-04-14 (105 days ago) Retirement: 2026-06-15 (43 days ago)
The provider has not named a replacement. Use suggest_replacement for options. Pricing/limits: $3/1M in · $15/1M out
Source: https://docs.anthropic.com/en/docs/about-claude/model-deprecations Provider's own term: "Retired"
Deadlines are always given in days, because a model cannot reliably judge whether 2026-07-30 is soon.
Design notes
A failed lookup is never a safety verdict. If the catalog is unreachable, the tool returns an MCP error and says so. An agent that read a network failure as "no deprecation found" would happily ship a retired model id. A model that simply isn't tracked gets the same treatment: it returns "not in the catalog, verify with the provider", never "OK".
Pass whatever string is literally in the code (gpt-4o, anthropic/claude-opus-4-1, azure/gpt-4o) and it resolves to the canonical tracked model.
When the provider's own deprecation notice names a successor, that is what you get. Otherwise the fallback list of same-provider active models is labelled as candidates to evaluate, so an agent can tell the two apart.
Anything past its retirement date is broken now, so it gets its own heading instead of sitting in "retiring soon".
Configuration
Both variables are optional.
| Variable | Default | Purpose |
|---|---|---|
LLMINTEL_API_KEY | none | Raises the rate-limit budget. The catalog itself is public, so you do not need this. |
LLMINTEL_BASE_URL | https://llmintel.ai | Point at a self-hosted or staging catalog. |
Anonymous callers get 30 requests/minute per IP, enough for interactive agent use.
Data provenance
Every record links to the provider page it was parsed from and preserves the provider's verbatim lifecycle term (sourceTerm), so a normalization decision is always auditable. Changes go through a human verification queue before publication. Collector freshness is public at /v1/status.
The same data is available as a plain REST API, also without a key. See llmintel.ai/docs.
Where to find it
| Directory | Entry |
|---|---|
| Official MCP Registry | ai.llmintel/model-lifecycle |
| Glama | @hivemindunit/llmintel-mcp |
| Smithery | llmintel/model-lifecycle |
| npm | @llmintel/mcp |
Development
pnpm --filter @llmintel/mcp build
pnpm exec vitest run packages/mcp # protocol-level tests against a fake catalog
Drive the built binary against a live catalog
pnpm --filter @llmintel/mcp smoke LLMINTEL_BASE_URL=http://localhost:3000 pnpm --filter @llmintel/mcp smoke
License
MIT © LLMIntel