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finops -resources

AI for FinOps: Curated collection of MCP servers and resources for Cloud FinOps practitioners

Installation
Run this command in your terminal to add the MCP server to Claude Code.
Run in terminal:
Command
claude mcp add --transport stdio optimnow-finops-mcp-resources docker run -i optimnow/finops-mcp-resources:latest \
  --env API_KEY="optional-api-key-for-finops-mcp-resources" \
  --env LOG_LEVEL="info" \
  --env SERVER_NAME="optimnow-finops-mcp-resources"

How to use

This MCP server implements a suite of FinOps resources for cloud cost management, including pricing insights, budgets, anomaly detection, and automation with built-in security guardrails. Once deployed, the server exposes capabilities that allow an AI client to fetch pricing data from supported cloud providers, monitor budget thresholds, flag cost anomalies, and trigger automated actions (such as alerts or remediation steps) within governed boundaries. Use cases include real-time cost tracking, budget adherence checks across multiple accounts, anomaly notification workflows, and automated optimization suggestions guided by guardrails to prevent unsafe actions.

To interact with the server, connect your MCP client to the containerized service. The server exposes endpoints for retrieving pricing models, querying budget data, running anomaly checks, and invoking automation routines. For typical workflows, you can start by querying current spend projections, setting up budget alerts, enabling anomaly detection rules, and configuring automated remediation playbooks. Documentation and example prompts provided with the repository walk you through composing requests and interpreting responses, including best practices for secure operation and role-based access control.

How to install

Prerequisites:

  • Docker or a compatible container runtime installed on your host (Docker Desktop for Windows/macOS, or docker-engine on Linux)
  • Basic networking access to pull images from your registry

Installation steps:

  1. Ensure Docker is running on your machine.

  2. Pull and run the MCP resources image using Docker:

    docker run -it --rm optimnow/finops-mcp-resources:latest

  3. If you require environment variables, provide them at container startup. For example:

    docker run -it --rm
    -e SERVER_NAME=optimnow-finops-mcp-resources
    -e API_KEY=your-api-key
    -e LOG_LEVEL=info
    optimnow/finops-mcp-resources:latest

  4. Verify the server is accessible from your MCP client and consult the repository’s tutorials for wiring the client to this server.

  5. Optionally, pin a specific image tag to ensure reproducibility (e.g., optimnow/finops-mcp-resources:1.0.0).

Additional notes

Tips and common issues:

  • If the container fails to start, check that Docker can access the image registry and that there are no port conflicts in your network. Ensure necessary environment variables (like API keys) are provided if required by your deployment environment.
  • Use the LOG_LEVEL environment variable to control verbosity for troubleshooting.
  • For production deployments, consider running behind a reverse proxy or API gateway and enable TLS to secure MCP communications.
  • Review the repository’s governance and security guidelines to ensure guardrails are properly configured for automated actions.
  • If you update the MCP resources image, test in a staging environment before promoting to production to avoid breaking change risks.

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