mcpbeat

LMX Cloud LLM Inference MCP Server

io.lmxcloud/mcp-server
answering

LMX Cloud LLM Inference is answering right now. Last checked moments ago. It exposes 8 tools.

OpenAI-compatible LLM MCP (7 tools); chat via balance key or x402 USDC on Base

Uptime history 42 hours of history
42 hours agonow
100.0%
Uptime 24h
92 of 92 checks
8
Tools
read from the server
306 ms
Response time
average over 24h
open, no key
Access
streamable-http

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 0 min ago.

run in your terminal
claude mcp add mcp-server --transport http https://mcp.lmxcloud.io/mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "mcp-server": {
      "url": "https://mcp.lmxcloud.io/mcp"
    }
  }
}
~/.codex/config.toml
[mcp_servers.mcp-server]
url = "https://mcp.lmxcloud.io/mcp"
.cursor/mcp.json
{
  "mcpServers": {
    "mcp-server": {
      "url": "https://mcp.lmxcloud.io/mcp"
    }
  }
}
.vscode/mcp.json
{
  "mcpServers": {
    "mcp-server": {
      "url": "https://mcp.lmxcloud.io/mcp"
    }
  }
}

Available tools 8

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

balance
get_balance
Fetch USD credit balance for the caller API key. Requires authentication.
chat
chat_completion
Call LMX Cloud OpenAI-compatible chat completions. Prefers a pre-funded API key (Bearer / api_key); when omitted and x402 is enabled, requires a USDC pay-per-call payment. Optional image_url / images enable vision input (OpenAI content-parts format) — use a vision model such as llama-3.2-90b-vision, qwen-3.6-35b, or qwen-3.5-35b.
models
list_models
List currently supported LMX model aliases and providers.
pricing
get_pricing
Fetch current LMX Cloud per-call pricing catalog.
quote
quote_price
Estimate USDC cost for a single model call. Uses GET /v1/pricing with model and token params.
status
get_status
Fetch LMX Cloud provider health, fallback chain, and anchoring status.
usage
get_usage
Fetch request and token usage totals for the caller API key. Requires authentication.
web
web_search
Real-time web search via LMX (Brave Search passthrough). Fixed per-call USDC price from the caller's API key balance. Returns title/url/snippet results.

Endpoints

URLTransportStateLatencyChecked
https://mcp.lmxcloud.io/mcp streamable-http answering 289 ms 0 min ago

LMX Cloud LLM Inference — questions

Answers built from our own checks of this server.

What can LMX Cloud LLM Inference do?
It exposes 8 tools, read directly from the server on our last check. Among them: chat_completion, get_balance, get_pricing, get_status, get_usage, list_models and 2 more. 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 LMX Cloud LLM Inference working right now?
We send a real MCP handshake every 15 minutes. Over the last 24 hours 92 of 92 checks got a reply (100.0%), average response time 306 ms. The bar chart above shows every period we have measured.
How do I connect LMX Cloud LLM Inference?
Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.
Does LMX Cloud LLM Inference need an API key?
No. LMX Cloud LLM Inference completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 8 of them are readable on this page. This is what we observed, not what the docs claim.
How fast is LMX Cloud LLM Inference?
It answers our handshake in 306 ms on average, which is faster than 46% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.