Llmxray MCP server
io.github.LogneBudo/llmxray·v0.8.12·23 starsWhat went wrong with your own Ollama calls, in sentences with the fix. Local, read-only.
not scanned yet
23 stars482 downloads/wk
Reviews
Write oneNobody has reviewed Llmxray yet.
If you have run it, two minutes of your experience saves the next person an afternoon.
Llmxray tools
No tool declarations could be read from the package source. They show once the server is installed.
How Llmxray compares
Against every graded MCP server, from our own scans and uptime checks. Updated after each scan run.
- Safety score
- 66/100
- higher than 23% of 48,255 servers
- GitHub stars
- 23
- more than 91% of 28,688 servers
- Downloads a week
- 482
- more than 87% of 12,191 servers with a package
Release history: 4 versions in the registry since 2026-10-15, latest 2026-10-23, typically one every 1 day.
Install Llmxray in Claude Code, Cursor or VS Code
Runs npx -y llmxray on your machine. Read the scan report first; the gateway never runs local packages.
claude mcp add llmxray -- npx -y llmxray
What the publisher says
From the Llmxray repository's README, as published. We do not edit it. Read it on GitHub
LLMxRay See what your local AI is actually doing. One command, one browser tab. Token-by-token streaming, cache diagnostics, model comparison, benchmarks and cost tracking for the models running on your own machine through Ollama. No cloud. No API keys. No cost.
🌐 English • Français • 中文 • العربية • Srpski
Quick Start • What it shows you • Who is this for • Install • Ollama compatibility • Changelog
Quick Start
You need Ollama running with at least one model pulled (ollama pull llama3.2). Then:
npx llmxrayOr with Docker:
docker run -p 5174:5174 djovaneli/llmxrayOpen http://localhost:5174. Pick a model, send a message, and watch what happens. That's it.
What LLMxRay shows you
You run a local model. You chat with it. LLMxRay answers the questions that come next: how fast was each token, what did the prompt cost, did the cache help, which setting was actually better, and what are your other tools sending to the same model.
Every page below is one of those answers.
Chat, token by token
Every token is drawn as it arrives, coloured by confidence. You see where the model hesitated and where it was sure. Markdown, multi-turn, file and image attachments, slash commands, and a thinking budget for reasoning models (off, model's choice, or low / medium / high / max).
Each response is also checked as it lands. A badge appears only when something is wrong: repetition, a refusal, gibberish, an empty answer, or a reply cut off at the token limit.
Session deep dive
Open any turn to see it as a timeline: time to first token, inter-token gaps, the reasoning block if there was one, tool calls, and the exact prompt that was sent.
Live: what your other tools send
LLMxRay opens a second port, 11435, that behaves exactly like Ollama and forwards everything to it. Point VS Code Copilot, Open WebUI, Continue, n8n or your own script at http://localhost:11435 and every turn they send appears here: client, model, prompt size, how much came from the cache, prefill and generation speed, tool calls.
Shortened. The full README is on GitHub.
Nothing above is checked by us. What we check is on the safety report.
Llmxray: common questions
- Is Llmxray MCP server safe?
- With care: it is graded C, so read the findings first (66/100). Read the Llmxray safety report
- How do I install Llmxray?
- It runs on your machine. Copy the Claude Code, Cursor, VS Code or Claude Desktop config from the install section.
- Does Llmxray need an API key?
- No secret keys are declared. It reads 2 settings from the environment.
- Is Llmxray maintained?
- The last commit was 20 days ago (2026-10-15). The latest release is v0.8.12.
- How does Llmxray compare with other MCP servers?
- safety score 66/100 (higher than 23% of 48,255 servers); github stars 23 (more than 91% of 28,688 servers); downloads a week 482 (more than 87% of 12,191 servers with a package). Full comparison.