LLM Latency Tracker MCP server

LLM Latency Tracker

Independent, provider-neutral latency & uptime for AI inference APIs — measured, not scraped.

🌐 Live: llmlatency.dev · 📊 JSON API · 🤖 MCP server · 🗓️ Deprecation calendar

Most "AI API latency" numbers come from the providers themselves, or from a benchmark run once and never updated. This project measures it continuously, from multiple regions, and publishes the result as an open dataset.

• Edge latency — full DNS → TCP → TLS → time-to-first-byte, measured with the Python standard library (no API key required).
• Inference latency — real time-to-first-token via a streaming request (optional, needs a provider key).
• Uptime — success rate per provider, per region.
• Regions — Europe (Germany), US (Central), Asia (Tokyo), South America (São Paulo). More welcome.
• ~45 providers — OpenAI, Anthropic, Google, Mistral, DeepSeek, xAI, Groq, Together, Fireworks, Cerebras, OpenRouter, Perplexity, plus Chinese models (GLM/Zhipu, Kimi/Moonshot, Qwen, MiniMax) and many more.
• Deprecation calendar — upcoming model retirements + migration targets, verified from official provider docs.

The site is a self-updating static site (Cloudflare Pages). The value isn't the code — it's the continuously-accumulated, distributed measurement archive. The code is open so the methodology is transparent.

For developers

# All regions, provider rankings for the last 24h — measured latency + uptime:
curl https://llmlatency.dev/api/rankings.json

• JSON API: /api/rankings.json · OpenAPI: /openapi.json
• Any page as Markdown: send Accept: text/markdown to any page URL, or append .md.
• For LLM ingestion: /llms.txt (index) and /llms-full.txt (full corpus).
• License: data is CC-BY-4.0 — free to use with attribution.

For AI agents

There's a real MCP server (Streamable HTTP) exposing a getaiapi_latency tool backed by the live data:

curl -X POST https://llmlatency.dev/mcp \
  -H 'Content-Type: application/json' \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/call",
       "params":{"name":"get_ai_api_latency","arguments":{"region":"eu-hetzner"}}}'

Run the MCP server locally

The hosted endpoint above needs no setup. If you prefer a local stdio server (or want to build it from source), mcp_server.py is a dependency-free proxy over the same public JSON API:

python3 mcp_server.py            # stdio MCP, stdlib only
# or
docker build -t llm-latency-mcp . && docker run -i llm-latency-mcp

Also available: an MCP Server Card (/.well-known/mcp/server-card.json), a browser WebMCP tool, an API catalog (RFC 9727) and an Agent Skills index. Regions: eu-hetzner, us-central, ap-tokyo, sa-east (omit for all).

How it works

Shortened. The full README is on GitHub.