Omni Lpr
Add automatic license plate recognition to agent-driven apps via a local PyPI MCP server on streamable HTTP.
Overview
io.github.habedi/omni-lpr is a MCP server for the Build phase that provides automatic license plate recognition over local streamable-http for AI agents.
What is this MCP server?
- PyPI package omni-lpr (v0.3.4) with streamable-http transport
- Local MCP endpoint default http://127.0.0.1:8000/mcp/
- Automatic license plate recognition tools for coding agents
- Python ecosystem deployment via pypi registry
- Open-source implementation on GitHub habedi/omni-lpr
- Package omni-lpr version 0.3.4 on PyPI
- Default transport URL http://127.0.0.1:8000/mcp/ (streamable-http)
- Server schema version 0.3.4 per manifest
Community signal: 25 GitHub stars.
What problem does it solve?
Building LPR into an agent-assisted prototype usually means custom Python vision glue instead of a ready MCP tool your client can call.
Who is it for?
Solo developers building access-control, parking, or logistics prototypes who want local LPR wired into Claude Code or Cursor.
Skip if: Production ANPR at scale without your own ops stack, or builders who cannot run a local Python MCP service.
What do I get? / Deliverables
After you run omni-lpr locally and register http://127.0.0.1:8000/mcp/, your agent can perform license plate recognition through standard MCP requests.
- Running local LPR MCP endpoint on port 8000
- Agent-callable plate recognition results for app prototypes
- PyPI-based integration without custom OCR scaffolding per session
Recommended MCP Servers
Journey fit
LPR is typically embedded as a vision integration while you are building parking, fleet, or access-control features. Omni LPR exposes recognition as an MCP service your agent calls, which is classic third-party capability wiring under integrations.
How it compares
Local vision MCP integration, not a cloud OCR marketplace or generic image-description skill.
Common Questions / FAQ
Who is io.github.habedi/omni-lpr for?
It is for builders using MCP-enabled agents who need on-machine automatic license plate recognition during product integration work.
When should I use io.github.habedi/omni-lpr?
Use it while building features that must read plates from images or video streams and you want the agent to call LPR as an MCP tool.
How do I add io.github.habedi/omni-lpr to my agent?
Install and start the omni-lpr PyPI service, then add the streamable-http MCP URL http://127.0.0.1:8000/mcp/ in your agent MCP settings.