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AI Model Watch

NPM · @AIMODELWATCH/MCP · SCANNED SEP 20

Prices, context windows, lifecycle and deprecation dates for 270+ AI/LLM models. Daily, no key.

Available components

66 Trust /100
Trust breakdown (7 categories)

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. How we score → Why this is hard to score →

Supply Chain Security100
  • No malware found by supply-chain analysis.Pass
  • No known CVEs affecting this package version or its production dependencies.Pass
  • No install/post-install scripts declared.Pass
  • 0 of 3 dependencies flagged as unhealthy. View diagnostics → Pass
Provenance & Transparency19
  • Repository check failed: the declared repository URL returned HTTP 404. See how to fix → View diagnostics → Fail
  • Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
  • Clear OSI-approved license (MIT).Pass
  • Actively maintained (last published 0 days ago).Pass
  • Security-disclosure policy not yet verified: we couldn't inspect the source repository.Unverified
Schema Quality & AI Usability86
  • 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).Pass
  • AI-judged instruction clarity (excellent).Pass
  • Context-footprint check failed: tool/resource definitions use about 1213 tokens (~110/item across 11 items; 9 tools + 2 resources), over budget; trim descriptions and params. See how to fix → Fail
  • Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
  • Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage89
  • 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
  • 63% of tool parameters carry a description.Partial
  • Structured output schemas are declared (100% of tools); any adoption earns full credit.Pass
Tool Safety100
  • No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
  • We read all 9 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
  • An AI judge read all 11 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
  • Implements a current MCP spec version (2026-07-28).Pass

Unverified: 1 category

A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

Install

How do I install the AI Model Watch MCP server?

AI Model Watch runs locally as an npm package, launched with npx -y @aimodelwatch/mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

npm · @aimodelwatch/mcp

# add to Claude Code
claude mcp add khavel-aimodelwatch -- npx -y @aimodelwatch/mcp
// .cursor/mcp.json
{
  "mcpServers": {
    "khavel-aimodelwatch": {
      "command": "npx",
      "args": [
        "-y",
        "@aimodelwatch/mcp"
      ]
    }
  }
}
// .vscode/mcp.json
{
  "servers": {
    "khavel-aimodelwatch": {
      "command": "npx",
      "args": [
        "-y",
        "@aimodelwatch/mcp"
      ]
    }
  }
}
# add to Codex CLI
codex mcp add khavel-aimodelwatch -- npx -y @aimodelwatch/mcp
// opencode.json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "khavel-aimodelwatch": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@aimodelwatch/mcp"
      ],
      "enabled": true
    }
  }
}
# add to OpenClaw
openclaw mcp add khavel-aimodelwatch --command npx --arg -y --arg @aimodelwatch/mcp
# ~/.hermes/config.yaml
mcp_servers:
  khavel-aimodelwatch:
    command: "npx"
    args: ["-y", "@aimodelwatch/mcp"]
// ~/.netclaw/config/netclaw.json
{
  "McpServers": {
    "khavel-aimodelwatch": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@aimodelwatch/mcp"
      ]
    }
  }
}
# add to Vellum
assistant mcp add khavel-aimodelwatch -t stdio -c npx -a -y @aimodelwatch/mcp
// mcp.json
{
  "mcpServers": {
    "khavel-aimodelwatch": {
      "command": "npx",
      "args": [
        "-y",
        "@aimodelwatch/mcp"
      ]
    }
  }
}
Changelog

Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.

  • 20 Sept 26 66

    First indexed and scored.

Diagnostics

Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.

Captured 20 Sept 2026 · Analysed npm/@aimodelwatch/mcp@2.0.1

Provenance No attestation

The registry publishes no build provenance for this version, so there is nothing to verify.

Result No attestation
Ecosystem npm

Background: How many MCP packages publish verified provenance →

Dependencies 3 packages
Packages resolved 3
Tree resolution Complete

Background: SBOMs and build attestations, explained →

MCP tools · 9 exposed · ~1,045 tokens

The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →

Tool Tokens
cheapest_models ~108

The N cheapest models by blended price (mean of input and output USD per 1M tokens). Only models with both prices published. Defaults to active models; pass status to widen.

NameTypeReqDescription
countinteger
modalitystringe.g. 'text', 'image', 'embedding'
providerstringProvider name, case-insensitive substring: 'openai', 'anthropic', 'google', 'mistral'...
statusstring
NameTypeReqDescription
modelsarrayyes
updatedstringyes

No examples provided.

check_model_status ~98

Is this model id safe to pin? Reports the provider-declared lifecycle status, the deprecation/retirement dates, days until retirement, and the stated replacement (with its row). A model absent from the catalog is reported as found=false, not as retired.

NameTypeReqDescription
idstringyesModel id or api_string, e.g. 'gpt-4o', 'claude-3-5-sonnet-20241022'
NameTypeReqDescription
api_stringstring|nullyes
days_to_retirementnumber|nullyes
deprecated_onyes
foundbooleanyes
idstring|nullyes
lifecycleyes
namestring|nullyes
replacementstring|nullyes
replacement_modelyes
retires_onyes
source_urlstring|nullyes
statusyes
suggestionsarrayyes
updatedstringyes

No examples provided.

compare_models ~41

Side-by-side rows for 2-6 models (by id or api_string) plus blended price per 1M tokens.

NameTypeReqDescription
idsarrayyes
NameTypeReqDescription
modelsarrayyes
not_foundarrayyes
updatedstringyes

No examples provided.

feed_freshness ~56

How current is the data: the catalog `updated` date, its age in days, model/deprecation counts, providers covered, and this server's cache state. Free to call; hits the network at most once per TTL.

Input schema present but exposes no named parameters.

NameTypeReqDescription
as_ofstringyes
cacheobjectyes
days_since_updateintegeryes
deprecation_countintegeryes
feed_updatedstringyes
feed_urlsobjectyes
licensestringyes
model_countintegeryes
providersarrayyes
updatedstringyes

No examples provided.

get_model ~90

Full catalog row for one model, looked up by id (slug) or api_string, case-insensitive. Includes notes, knowledge cutoff and the official source_url. When not found, returns found=false plus up to 5 similar ids.

NameTypeReqDescription
idstringyesModel id or api_string, e.g. 'claude-opus-4-8' or 'gpt-5.6'
NameTypeReqDescription
foundbooleanyes
modelyes
suggestionsarrayyes
updatedstringyes

No examples provided.

list_deprecations ~191

Every deprecation/retirement a provider has declared, with dates, days to retirement and the stated replacement. 'upcoming' = not yet retired (dated in the future, or undated); 'past' = already retired. Sorted soonest retirement first; undated rows last.

NameTypeReqDescription
afterstringKeep rows retiring (or, if undated, deprecated) on/after this date
as_ofstringReference date for upcoming/past and day counts; defaults to today (UTC)
beforestringKeep rows retiring (or, if undated, deprecated) on/before this date
limitinteger
offsetinteger
providerstringProvider name, case-insensitive substring: 'openai', 'anthropic', 'google', 'mistral'...
whenstring
NameTypeReqDescription
as_ofstringyes
countintegeryes
deprecationsarrayyes
next_offsetyes
offsetintegeryes
totalintegeryes
updatedstringyesDate the catalog last changed (feed `updated`)

No examples provided.

list_models ~202

List models from the catalog with optional filters and pagination. Returns summary rows (no notes); call get_model for the full row. Filters combine with AND.

NameTypeReqDescription
limitinteger
modalitystringSubstring match on the modality tags, e.g. 'text', 'image', 'audio', 'video', 'pdf', 'code'
offsetinteger
open_weightbooleantrue = open-weight models only, false = closed only
providerstringProvider name, case-insensitive substring: 'openai', 'anthropic', 'google', 'mistral'...
querystringCase-insensitive text search over id, name and api_string
statusstringLifecycle status as the provider states it: 'ga', 'preview', 'beta', 'deprecated', 'retired'. 'active' is shorthand for ga+preview+beta (still callable).
NameTypeReqDescription
countintegeryes
modelsarrayyes
next_offsetyes
offsetintegeryes
totalintegeryes
updatedstringyesDate the catalog last changed (feed `updated`)

No examples provided.

models_changed_since ~195

Lifecycle events dated on/after a date, newest first: launches (released), deprecation announcements (deprecated_on) and retirements that have happened (retires_on). Built from the dated fields on each catalog row; the feed has no per-field modification timestamps, so price changes are not visible here (see aimodelwatch.dev/changelog). Retirements scheduled after today are omitted unless include_scheduled=true (use list_deprecations when=upcoming for those). Also returns the feed `updated` date so you can tell whether the catalog moved at all.

NameTypeReqDescription
include_scheduledbooleanAlso list retirements dated in the future (event "retires")
limitinteger
providerstringProvider name, case-insensitive substring: 'openai', 'anthropic', 'google', 'mistral'...
sincestringyesYYYY-MM-DD, inclusive
NameTypeReqDescription
as_ofstringyes
countintegeryes
eventsarrayyes
notestringyes
sincestringyes
totalintegeryes
updatedstringyes

No examples provided.

search_models ~64

Free-text search across id, name, provider, api_string AND the notes field (the notes carry batch prices, cache tiers, hosting availability...). For structured filtering prefer list_models.

NameTypeReqDescription
limitinteger
querystringyesAll whitespace-separated terms must match
NameTypeReqDescription
modelsarrayyes
totalintegeryes
updatedstringyes

No examples provided.

Common questions

What is the AI Model Watch MCP server?

AI Model Watch is an MCP server listed in the public MCP registry as io.github.Khavel/aimodelwatch. Prices, context windows, lifecycle and deprecation dates for 270+ AI/LLM models. Daily, no key. This page covers its npm package (@aimodelwatch/mcp).

Is the AI Model Watch MCP server safe to use?

AI Model Watch scores 66 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 20 September 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

What tools does the AI Model Watch MCP server expose?

AI Model Watch exposes 9 tools: list_models, get_model, search_models, compare_models, cheapest_models, and 4 more. Their descriptions and schemas cost roughly 1,045 tokens of context every time the server is loaded.

Is the AI Model Watch MCP server still maintained?

AI Model Watch is still listed as active in the MCP registry. We last reached this channel on 20 September 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

What licence is the AI Model Watch MCP server under?

AI Model Watch declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.