Server data from the Official MCP Registry
Search Sunex lenses and imager sensors, match compatible optics, get pricing. No API key needed.
About
Search Sunex lenses and imager sensors, match compatible optics, get pricing. No API key needed.
Remote endpoints: sse: https://mcp.sunex-ai.com/sse
Security Report
Valid MCP server (1 strong, 1 medium validity signals). 5 known CVEs in dependencies Imported from the Official MCP Registry. 1 finding(s) downgraded by scanner intelligence.
Endpoint verified · Open access · 6 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Connect
Remote Plugin
No local installation needed. Your AI client connects to the remote endpoint directly.
Add this to your MCP configuration to connect:
{
"mcpServers": {
"com-sunex-optics-mcp": {
"url": "https://mcp.sunex-ai.com/sse"
}
}
}Documentation
View on GitHubFrom the project's GitHub README.
Sunex Optics MCP Server
A public Model Context Protocol server that lets AI assistants search Sunex's lens and imager catalog in natural language.
Live endpoint: https://mcp.sunex-ai.com/mcp
Landing page: sunex-ai.com
Transport: Streamable HTTP (MCP spec 2025-03-26). Legacy SSE endpoint at /sse preserved for older clients.
Connect in 30 seconds
Claude
Settings → Connectors → Add custom connector → paste https://mcp.sunex-ai.com/mcp
Cursor / Continue / Zed
Add to your MCP config with transport streamable-http and the URL above.
ChatGPT
Via any MCP → OpenAPI bridge as a custom GPT Action.
Five tools
| Tool | What it does |
|---|---|
recommend_lens_for_imager | Give it an imager PN → compatible lenses with FOV and angular resolution. One shot. |
search_imagers | Find sensors by PN, manufacturer, or resolution class. |
get_imager_detail | Full sensor specs plus computed geometry (width / height / diagonal in mm). |
find_compatible_lenses | Given pixel count + pitch, return lenses whose image circle covers the sensor. |
search_products | Full catalog search by PN or keyword, with sample pricing and RFQ links. |
Example prompts
- "Recommend a wide-angle lens for the Sony IMX577 with F/2.0 or faster."
- "I need fisheye lenses under $100."
- "What's the diagonal of the IMX477 in mm?"
- "Find lenses for a 1920×1080 sensor with 3µm pixels, 100–180° HFOV."
Architecture
Claude / Cursor / ChatGPT → mcp.sunex-ai.com → optics-online.com/api/v1
(MCP client) (Cloudflare Worker) (ASP JSON API)
Thin proxy on Cloudflare Workers (free tier) over Sunex's production catalog. Streamable HTTP transport per MCP spec 2025-03-26 (with legacy SSE preserved). No auth, read-only.
Endpoints
| Path | Purpose |
|---|---|
/mcp | Primary — Streamable HTTP transport (current MCP standard) |
/sse | Legacy SSE transport, preserved for backward compatibility |
/.well-known/mcp.json | Public discovery manifest |
/ | Landing page with install instructions |
Self-host
git clone https://github.com/Sunex-AI/Optics-mcp
cd Optics-mcp
npm install
npx wrangler login
npx wrangler deploy
Calling a tool directly (Python)
from mcp import ClientSession
from mcp.client.streamable_http import streamablehttp_client
async with streamablehttp_client("https://mcp.sunex-ai.com/mcp") as (r, w, _):
async with ClientSession(r, w) as session:
await session.initialize()
result = await session.call_tool(
"recommend_lens_for_imager",
{"imagerPn": "IMX577", "fNumMax": 2.0}
)
Discovery
Public manifest: https://mcp.sunex-ai.com/.well-known/mcp.json
Contributing
Issues and PRs welcome. For requests about the backend API (pricing, additional catalog fields, new endpoints), email support@sunex.com.
License
MIT — see LICENSE.
Reviews
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