Optometry Ai Safety automation via MCP. Includes classify optometry device, check fda samd, ...
Optometry MCP server exists for a simple reason — assistants are far more useful when they can act on Optometry directly instead of describing what you should do. Optometry Ai Safety automation via MCP. Includes classify optometry device, check fda samd, ...
This MCP server is built with EU AI Act compliance built-in:
Once Optometry is connected, these are the calls the assistant has available:
Real — time AI safety monitoringMulti — agent governancePro — ** $99/mo — Full MCP suite + EU AI Act trackingEnterprise — ** $499/mo — Custom dev + SLA + Dedicated supportDomain — PurposeTier — Price@smithery/cli on npm is all you need. Most clients run it directly, so configuration is a few lines and a restart.
Plenty of monitoring and observability servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Optometry's toolset — Real, Multi, Pro and 3 more — is a fair guide to whether it matches your workflow. It is maintained by CSOAI-ORG; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Real | time AI safety monitoring |
| Multi | agent governance |
| Pro | ** $99/mo — Full MCP suite + EU AI Act tracking |
| Enterprise | ** $499/mo — Custom dev + SLA + Dedicated support |
| Domain | Purpose |
| Tier | Price |
{
"mcpServers": {
"optometry-ai-safety": {
"command": "npx",
"args": ["-y", "@smithery/cli"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Give your coding agent the full DevTools toolbox: traces, network, console, heap snapshots and Lighthouse.
Dashboards, Prometheus and Loki queries, incidents and alerts — observability by conversation.
Errors with full context — stack traces, issue triage and AI-powered root-cause analysis from Sentry's server.
Enables enhanced web research capabilities for large language models through intelligent search queuing and advanced content extraction.
Automates browser interactions and enables Large Language Models (LLMs) to interact with web pages through Playwright and Chrome DevTools Protocol
Guides tool usage by providing recommendations for MCP tools at each problem-solving stage.