Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@model-version-mcp show me recent OpenAI models with pricing"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server that provides up-to-date AI model names and pricing from models.dev.
Solves the problem of AI models hallucinating outdated model names by providing a live-fetched, filtered list of recently released models.
get_ai_modelsReturns AI models released within the last 4 months with pricing data.
Parameters:
provider (optional): Filter by provider name, e.g. "anthropic", "openai", "google"
Returns: JSON with model id, name, provider, release_date, cost ($/1M tokens), context window, and capabilities.
Related MCP server: token-scout
git clone <repo>
cd model-version-mcp
npm install
npm run build
claude mcp add --transport stdio model-version-mcp node dist/index.jsAdd to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"model-version-mcp": {
"command": "node",
"args": ["/absolute/path/to/model-version-mcp/dist/index.js"]
}
}
}models.dev — community-maintained, no API key required. Cache refreshes every 60 minutes.
Returns current AI models (released within last 4 months) with pricing. Use this to get accurate, up-to-date model IDs instead of guessing.
Inputs: provider.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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Scored across 1 tool
With only a single tool, there is no possibility of confusing it with another tool. The purpose of get_ai_models is clearly isolated and unambiguous.
The sole tool name follows a consistent verb_noun pattern (get_ai_models), which is clear and descriptive. There are no mixed conventions since only one name exists.
A single tool feels thin for an MCP server, even if the scope is narrowly focused on retrieving current AI models. While it can serve as a simple read-only utility, users might expect additional related operations given the server name.
The tool provides a core way to fetch recent AI models with pricing, but it lacks support for retrieving specific model details or older models outside the 4-month window. These gaps could force agents to work around the limitation or fail when needing historical model info.
Live registry of AI model specs, context windows, and per-token pricing.
Live pricing data for AI models across vendors: input/output prices per 1k tokens as JSON.
Sourced AI-model pricing and capability data — compare and route to the cheapest capable model.
Live prices, rankings, licences and privacy of AI models: best model per task, costs, alternatives.