What is Druva MCP?
Druva MCP (Model Context Protocol) is an enterprise integration standard connecting AI copilots—such as Anthropic Claude and Microsoft Copilot—directly to the Druva Resilience Cloud. It converts backup telemetry, cyber threat indicators, and governance metadata into an active intelligence layer for enterprise IT and security operations.
Key Value Propositions & Core Capabilities
Natural Language Operations: Execute backup health checks, compliance audits, and telemetry queries through natural language prompts instead of navigating complex UI dashboards.
Token-Efficient Intent Mapping: Uses a curated skills architecture to map user intent directly to specific operational workflows, drastically reducing Large Language Model (LLM) context overhead and latency compared to raw REST APIs.
Unified Context Graph: Powered by the Dru Metagraph, correlating backup metadata, admin activity, and threat indicators into structured relationships.
Enterprise Security Guardrails: Enforces role-based access control (RBAC) via 3-legged OAuth 2.1 authentication and blocks destructive operations (e.g., data deletion or policy alteration) at the protocol level.
Druva MCP Technical Architecture & Core Primitives
Unlike basic API wrappers, Druva MCP utilizes specific primitives and curated skills to map natural language directly into executable workflows:
Primitive / Method
| Technical Description
| Operational Function
|
list_skills
| Skill Discovery Endpoint
| Discovers available backup, recovery, governance, and operational workflows.
|
recommend
| Intent Classifier
| Maps natural language intent to specific skills, minimizing token bloat.
|
retrieve_skill
| Context Fetcher
| Obtains execution scripts, operational steps, and compliance guardrails.
|
run_script
| Hardened Executor
| Runs approved workflows safely inside isolated execution sandboxes.
|
Enterprise Security & Governance Framework
Safety and compliance are non-negotiable when connecting AI agents to enterprise infrastructure. Druva MCP is engineered with multiple safety guardrails:
Implicit RBAC via OAuth 2.1: The AI agent acts strictly on behalf of the logged-in user, inheriting their exact roles, tenant scopes, and resource permissions.
Blocked Destructive Actions: Destructive operations—such as deleting backup snapshots, disabling policies, or purging storage—are blocked at the protocol layer to prevent malicious or accidental execution.
Isolated Execution Environments: Workflows run inside hardened sandboxes with restricted network access to protect enterprise boundaries.
Cloud-Native Delivery: As a fully managed SaaS server, Druva MCP continuously delivers capability updates without requiring local software upgrades or plugin maintenance.
How do IT teams use Druva MCP for cyber incident response?
1. Backup Operations & Health Checks
2. Recovery Orchestration
Goal: Identify safe restore points during system failures or data corruption.
Prompt Example: "Find the most recent clean snapshot for the production SQL database prior to 09:00 AM yesterday and check recovery readiness."
3. Security & Cyber Incident Response
4. Audit & Policy Compliance
Step-by-Step Configuration & Deployment Guide
Connecting an AI agent to Druva MCP involves three primary deployment steps.
Step 1: Add the Regional MCP Server Endpoint
Add the Druva MCP URL to your client application's configuration file or GUI integration manager.
JSON Configuration (e.g., Claude Desktop / VS Code Extension):
{
"mcpServers": {
"druva": {
"type": "http",
"url": "https://mcp-us.druva.com/mcp"
}
}
}
TOML Configuration:
Ini, TOML
[mcp_servers.druva]
url = "https://mcp-us.druva.com/mcp"
For platforms with built-in integration interfaces, select Add Custom Connector and input your regional endpoint URL.
Step 2: 3-Legged OAuth 2.1 Authentication
Upon invoking your initial prompt, the MCP agent initiates a secure sign-in sequence:
The AI client opens a browser window that redirects to the Druva Authentication Portal.
Authenticate using your enterprise single sign-on (SSO) credentials, password, and Time-based One-Time Password (TOTP) multi-factor authentication.
OAuth 2.1 issues short-lived, scoped tokens back to the MCP server session.
Step 3: Validate Connection
Verify operational readiness by submitting the following test prompt within your AI client:
"List available Druva tools."
If the client lists tools without generating errors, your installation is configured and active.
Summary
The Druva Model Context Protocol (MCP) integration bridges enterprise AI copilots and data resilience infrastructure, transforming passive backup logs into an active intelligence layer. By replacing fragmented API endpoints with curated, intent-mapped workflows, it drastically cuts token overhead while enabling plain-language monitoring, rapid threat investigations, and automated compliance reporting.
Built-in enterprise guardrails—including OAuth 2.1-based access control, sandboxed execution, and strict protocol-level blocks on destructive actions—ensure that AI agents operate safely without risking data loss or policy violations.
Ultimately, Druva MCP empowers IT and security teams to maintain complete context, accelerate incident response, and simplify data governance directly within their existing AI tools.
For datasheets and full technical documentation, explore the official Druva MCP Datasheet or request a Druva Product Demo.
Related Resources & Further Reading
