Velero MCP Server

The Velero MCP Server is an open-source Model Context Protocol (MCP) server that exposes read-only, safe, structured access to Velero backup and schedule resources running inside any Kubernetes cluster.

It allows AI agents (ChatGPT, Claude, Cursor, GitHub Copilot, etc.) to:

• Inspect Velero backups
• Inspect Velero schedules
• Generate Velero Backup YAML manifests
• Access Velero data as MCP resources
• Safely interact with your cluster in read-only mode

This project helps platform engineers automate workflows using AI while ensuring zero-risk, low-privilege, and read-only access to critical cluster configuration.

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Why This Project Exists

Velero is commonly used for:

• Kubernetes namespace & cluster backups
• Disaster recovery
• Cluster migrations
• Persistent volume snapshot management

But until now, no MCP server existed to expose Velero CRDs to LLM-based tools in a safe, structured way.

This project provides:

• A consistent API for querying Velero
• Strong typed models
• Complete read-only safety
• Guaranteed LLM-friendly output
• Ready integration with GitOps

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Features

MCP Tools

list_velero_backups(namespace?: str)

Returns a list of Velero Backup CRs.

get_velero_backup(name: str, namespace?: str)

Returns a detailed structured backup object.

list_velero_schedules(namespace?: str)

Lists Velero Schedule CRs including cron, paused state, and last backup.

generate_velero_backup_yaml(...)

Generates read-only YAML for a Velero Backup.

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MCP Resource Endpoints

Resource	Description
velero://backups	All backups in default namespace
velero://schedules	All schedules in default namespace

These allow LLMs to explore Velero state without calling tools.

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Architecture

• Python 3.10+
• MCP (official Model Context Protocol SDK)
• Kubernetes Python Client
• Pydantic models
• Safe, read-only design
• No kubectl, no exec, no side effects

Flow:

MCP Client  Velero MCP Server  Kubernetes API  Velero CRDs

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Security Model

Designed to be 100% safe

The server never:

• Creates backups
• Runs restores
• Deletes backup objects
• Writes anything to Kubernetes

Only reads CRDs via the Kubernetes API.

RBAC Required:

get, list on:
- backups.velero.io
- schedules.velero.io

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Installation

git clone https://github.com/YOUR-ORG/velero-mcp-server.git
cd velero-mcp-server

python -m venv .venv
source .venv/bin/activate    # Windows: .venv\Scripts\activate

pip install -r requirements.txt
pip install .

For development:

pip install ".[dev]"

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Configuration

Environment Variables

Variable	Description	Default
KUBECONFIG	Path to kubeconfig	auto
VELERO_NAMESPACE	Velero namespace	velero

K8s auth order:

1. In-cluster ServiceAccount
2. $KUBECONFIG
3. ~/.kube/config

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Running the Server

Start the server in stdio mode (required by MCP):

python -m velero_mcp_server.server

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Example MCP Client Configuration

ChatGPT MCP configuration

{
  "mcpServers": {
    "velero-mcp": {
      "command": "python",
      "args": ["-m", "velero_mcp_server.server"],
      "env": {
        "KUBECONFIG": "/path/to/kubeconfig",
        "VELERO_NAMESPACE": "velero"
      }
    }
  }
}

Claude Desktop

"mcpServers": {
  "velero-mcp": {
    "command": "python",
    "args": ["-m", "velero_mcp_server.server"],
    "env": {
      "KUBECONFIG": "/path/to/kubeconfig",
      "VELERO_NAMESPACE": "velero"
    }
  }
}

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Example Usage (AI Agent)

List failed backups

Call list_velero_backups and filter phase = Failed.

Inspect a backup

Use get_velero_backup for prod-full and tell me included namespaces.

Generate a manifest

Generate a Velero backup YAML including namespaces db, logging, TTL=168h.

Produces:

apiVersion: velero.io/v1
kind: Backup
metadata:
  name: prod-backup
  namespace: velero
spec:
  includedNamespaces:
    - db
    - logging
  ttl: 168h

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Development

Run linters:

ruff check velero_mcp_server

Type-check:

mypy velero_mcp_server

Run tests:

pytest

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Contributing

We welcome contributions of all kinds:

• Add Velero Restore / VolumeSnapshot support
• Improve error handling
• Add more MCP resources
• Add a Helm chart
• Add logging or metrics
• Improve documentation

Read the full CONTRIBUTING.md.

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License

This project is licensed under the MIT License, allowing:

• Commercial use
• Private use
• Modification
• Distribution

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Roadmap

Planned improvements:

• Add support for Restore CRDs
• Snapshot objects
• Restore impact analysis
• Write-enabled mode (behind strict flags)
• Publish to PyPI
• Helm chart for cluster deployment

If you'd like to help shape the direction, please open an issue!