LLMIntel Model Lifecycle

Name: LLMIntel Model Lifecycle
Author: hivemindunit

by hivemindunitversion 0.2.0i★ –iComputer or cloud

Registry nameai.llmintel/model-lifecycle

Install

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 open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

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: 1 of 1 passed
Runs on the maker’s server: what you ask it goes through their server.
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?

ClaudeClaude CodeCursorVS CodeChatGPT

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/mcp

Or 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/mcp

Or 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/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": {
    "model-lifecycle": {
      "url": "https://llmintel.ai/v1/mcp"
    }
  }
}

Or run it on your computer

Open in Cursor

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.

Open in VS Code

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

Open in VS Code

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:

Open ChatGPT on the web → Settings → Connectors (Apps)
Press Create or Add (some plans need Developer mode under Advanced first)
Paste the address below, give it a name and save
If it asks you to sign in, sign in with the maker

https://llmintel.ai/v1/mcp

Menu 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

LLMINTEL_API_KEY secret env
Optional. The catalog is public and needs no key; supplying one only raises the rate-limit budget.
LLMINTEL_BASE_URL env
Optional. 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.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

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 6, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain llmintel.ai (the registry checks domain ownership)
… 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 checked yet
Endpoint responds
Not checked yet; we check endpoints in rotation
… Not checked yet
Sign-in with OAuth
Not checked yet; we check endpoints in rotation
… Not checked yet
No hidden instructions in tool descriptions
Not checked yet; we read the tool list when we check the endpoint

Compared with others in Search & AI memoryi

More stars than 0% of the other 7231 servers in this category
Published to the registry more recently than 25% of the other 7231 servers in this category
Basic checks equal to or better than 100% of the other 7231 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 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?

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 –, and the latest version (0.2.0) reached the registry 3 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 in developer mode.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated 3 days ago

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated 44 days ago

Install

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

LLMIntel Model Lifecycle

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Or run it on your computer

Or run it on your computer

Or run it on your computer

Or run it on your computer

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

@llmintel/mcp

Install

Cursor

Claude Code

Claude Desktop

Hosted endpoint (no install)

Tools

Example

Design notes

Configuration

Data provenance

Where to find it

Development

Drive the built binary against a live catalog

License