MCP server

XF Model Source

dev.xpansion/xfms

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

Find the right AI model for your job. Free discovery and ranking; tests on your own key.

Website Source

At a glance

Type

MCP server

Publisher

xpansion.dev (verified by the MCP Registry)

Status

Working at last check

Tools

7

Token cost

About 2,732 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http xfms https://xfms.xpansion.dev/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.xfms]
url = "https://xfms.xpansion.dev/mcp"

Gemini CLI

{"mcpServers":{"xfms":{"httpUrl":"https://xfms.xpansion.dev/mcp"}}}

Cursor

{"mcpServers":{"xfms":{"url":"https://xfms.xpansion.dev/mcp"}}}

VS Code

{"servers":{"xfms":{"type":"http","url":"https://xfms.xpansion.dev/mcp"}}}

Antigravity

agy mcp add xfms https://xfms.xpansion.dev/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"xfms","server_url":"https://xfms.xpansion.dev/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"xfms","server_url":"https://xfms.xpansion.dev/mcp"}

Tools

• benchmark ~617 tokens
  The live test: the 5 proven models and 1 promising newcomer from discovery do the person's real tasks side by side, every requirement is judged, and the results pick the winner. First call (session + tasks) returns the estimate and an offer — nothing is spent. Show the person the cost; only when the
• compare ~537 tokens
  Same live test as benchmark, but on the models the person names (model_ids). Needs a finished discover session so every requirement is judged. Estimate first, then go=true.
• discover ~705 tokens
  Discovery: finds the true requirements of the person's job before any model is chosen. Start with purpose: the reply carries the discovery instructions and the evidence catalogue. YOU ask the person the questions (one thing each, plain words, offering the returned choices); then call again with the
• field_results ~140 tokens
  Results from real comparisons on Model Source for one kind of job (call with no job_type for the list): which models passed, how often, which won, typical cost per task and the most common failure. Counted without anyone's job details. A starting point; test on the person's own work before choosing.
• pick ~123 tokens
  The single best proven model for a job worked out with discover, with why and the runners-up. Pass the discover session.
• rank ~151 tokens
  The full shortlist for a job worked out with discover: 5 proven models and 1 promising newcomer, each with its standing on every requirement, plus near misses and what would change the order. Pass the discover session.
• watch_job ~459 tokens
  Saves a finished job for XF Model Watch, which re-tests it as new models arrive and emails the person only when a model passes every must-have and ranks higher on their priorities. Needs a signed-in subscriber. Ask the person first: Model Watch keeps the job and its example tasks (encrypted, deletab

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