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Model Tested MCP Server

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Model Tested is answering right now. Last checked 8 min ago. It exposes 5 tools. Last commit 1 Nov 2026.

Independent test scores for open-weight LLMs: best model for your GPU or Mac, comparisons.

Uptime history 16 days of history
16 days agonow
100.0%
Uptime 24h
91 of 91 checks
5
Tools
read from the server
147 ms
Response time
average over 24h
0
Stars
last commit 1 Nov 2026

What the code does

We read the source, 1 d ago · tools taken from the live server · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

Runs an external command runner/local.py:56, runner/sandbox.py:68
        if subprocess.run(["ollama", "pull", m["ollama_tag"]]).returncode != 0:
Page loads a third-party script site/src/components/Comments.astro:10
  <script
    src="https://giscus.app/client.js"
Page executes code built at runtime site/src/pages/search.astro:35
        tmp.innerHTML = html;

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Three servers free · no card

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 8 min ago.

run in your terminal
claude mcp add llm-benchmarks --transport http https://modeltested.com/mcp
Settings → Connectors → Add custom connector, then paste this address
https://modeltested.com/mcp
~/.codex/config.toml
[mcp_servers.llm-benchmarks]
url = "https://modeltested.com/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "llm-benchmarks": {
      "url": "https://modeltested.com/mcp"
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "llm-benchmarks": {
      "type": "http",
      "url": "https://modeltested.com/mcp"
    }
  }
}

Available tools 5

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

articles
search_articles
Find Model Tested articles and ranking pages by keyword, newest first: news about newly tested models, guides on quantization, Ollama and memory. Returns title, summary, date and link.
compare
compare_models
Use this whenever the user asks how two or more open-weight models compare, or which of them to pick. Returns our test scores, rank and memory needs for 2 to 6 models side by side.
decision
decision_models
Use this whenever the user asks about decision models or LLMs for classification, routing, triage or yes/no calls. Accuracy on our decision test (routing tickets, applying rules, spotting phishing, flagging risky code changes), how well each model's confidence matches its accuracy (calibration), and API cost per 1,000 calls. Covers dedicated decision models and regular LLMs given the same tasks.
model
get_model
Use this whenever the user asks about a specific open-weight model: how good it is, its benchmark scores, whether it's worth using, how much VRAM or memory it needs, or which quantization to download. Returns our test scores, rank, memory at each quantization, the smallest GPU and Mac it fits, decision accuracy and our Q4 run on a Mac when there is one. Accepts a name or slug, e.g. 'qwen3.5 9b' or 'gpt-oss-20b'.
models
find_models
Use this whenever the user asks which local or open-weight LLM is best, overall or for coding, documents or decisions, or which model they can run on their graphics card (VRAM) or Mac. Returns tested models ranked by our own test scores, best first; with a GPU or Mac memory size it only returns models that fit, plus the quantization to download and the memory it needs. Examples: 'best model for a 16 GB GPU', 'best coding model on a 32 GB Mac', 'best small model under 10B'.

Endpoints

URLTransportStateLatencyChecked
https://modeltested.com/mcp streamable-http answering 101 ms 8 min ago

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Model Tested — questions

Answers built from our own checks of this server.

What can Model Tested do?
It exposes 5 tools, read directly from the server on our last check. Among them: compare_models, decision_models, find_models, get_model, search_articles. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →
Is Model Tested working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 147 ms. The bar chart above shows every period we have measured.
How do I connect Model Tested?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does Model Tested need an API key?
No. Model Tested completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 5 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is Model Tested?
It answers our handshake in 147 ms on average, which is faster than 83% of all working MCP servers we measure. That puts it in the quick quarter of the ecosystem. The comparison comes from our own checks across the whole registry, every 15 minutes.
Is Model Tested open source?
We cannot say either way: written in Astro, 0 stars on GitHub and 1 open issue, but we could not determine the licence, and without one the code is not open source by default.