jtaleric/orion-mcp
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Orion MCP is a Model Context Protocol server designed for performance regression analysis using the cloud-bulldozer/orion library.
Orion MCP
Orion MCP is a Model Context Protocol (MCP) server for performance regression analysis powered by the cloud-bulldozer/orion library.
Key Features
- Regression Detection – Automatically detects performance regressions in OpenShift & Kubernetes clusters.
- Interactive MCP API – Exposes a set of composable tools & resources that can be consumed via HTTP or by other MCP agents.
- Visual Reporting – Generates publication-ready plots (PNG/JPEG) for trends, multi-version comparisons and metric correlations.
- Container-first – Ships with a lightweight OCI image and an example OpenShift deployment manifest.
Table of Contents
Getting Started
Prerequisites
- Python 3.11 or newer
- An OpenSearch (or Elasticsearch ≥7.17) endpoint with Orion-indexed benchmark results
- Podman or Docker (optional – for containerised execution)
Installation (virtual-env)
# Clone repository
$ git clone https://github.com/YOUR_ORG/orion-mcp.git && cd orion-mcp
# Create & activate a virtual environment
$ python3.11 -m venv .venv
$ source .venv/bin/activate
# Install Python dependencies
$ pip install -r requirements.txt
Quick Start
Set the data-source endpoint and launch the server locally:
export ES_SERVER="https://opensearch.example.com:9200"
python orion_mcp.py # listens on 0.0.0.0:3030 by default
Available Tools
| Tool | Description | Default Arguments |
|---|---|---|
get_data_source | Returns the configured OpenSearch URL | none |
get_orion_configs | Lists available Orion configuration files | none |
get_orion_metrics | Lists metrics grouped by Orion config | none |
openshift_report_on | Generates a trend line for one or more OCP versions | versions="4.19", lookback="15", metric="podReadyLatency_P99", config="small-scale-udn-l3.yaml" |
has_openshift_regressed | Scans all configs for changepoints | version="4.19", lookback="15" |
metrics_correlation | Correlates two metrics & returns a scatter plot | metric1="podReadyLatency_P99", metric2="ovnCPU_avg", config="trt-external-payload-cluster-density.yaml", version="4.19", lookback="15" |
Deployment
Container Image
podman build -t quay.io/YOUR_ORG/orion-mcp:latest .
# or
docker build -t your-org/orion-mcp:latest .
OpenShift
A production-ready openshift-deployment.yml is provided:
# Update ES_SERVER env if required then apply
oc apply -f openshift-deployment.yml
# Verify
oc get pods -l app.kubernetes.io/name=orion-mcp
Expose the service using an OpenShift Route and point your MCP client to http://<host>:3030.
Development
# Run linters & tests
flake8
pytest
# Auto-format with black & isort
black . && isort .
Contributing
Pull requests are very welcome! Please ensure you have read and adhere to the Code of Conduct.
- Fork the repository
- Create a new branch for your feature or bugfix
- Make your changes and add tests if applicable
- Submit a pull request with a clear description of your changes
License
Orion-MCP is distributed under the Apache 2.0 License. See the file for full text.