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Open-source project

BRI

BRI exposes video analysis tools through a FastAPI MCP server, with SQLite job storage and a Streamlit interface.

Project details

Classification
Open-source project
Repository
Alexi5000/Bri
Language
Python
License
MIT
Status
Active development
Tests
3 test notes
Last verified
2026-08-03

What it is

I use BRI as an example of exposing video analysis tools through MCP. Whisper and YOLO tooling sit behind a FastAPI MCP server, SQLite stores job state, and Streamlit provides the interface. The README and workflow files describe setup and checks.

Architecture

  • FastAPI MCP server publishes the analysis tools with typed inputs.
  • SQLite provides durable job and result state without an external database dependency.
  • Separate Docker images for the MCP server and the UI so the tool surface can be deployed without the operator app.
  • Pre-commit hooks and a Makefile define local checks and run commands.

Tests and gates

  • Four workflows: ci, codeql, docs, and release.
  • Pre-commit configuration and markdownlint run over the repository.
  • GOVERNANCE.md, MAINTAINERS.md, and SECURITY.md define ownership and disclosure.

Limits

  • Results depend on the underlying models. The surrounding tools do not establish their accuracy.
  • SQLite durability suits single-node deployments; it is not a multi-writer data plane.
  • The MCP surface is unauthenticated by default and expects to run behind a trusted boundary.

Source files and examples

Related methods

Related projects

I document the project here. TechTide AI publishes current service scope, prices, and terms.

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