# MCP Order Management with RBAC

> MCP Order Management with RBAC — techakash32-mcp-order-management-with-rbac. Use this tool when you need to manage orders with role-based access control, solving problems of unauthorized access and inefficient order processing. It enables users to view and refund orders based on their permissions, with inputs including user credentials and order IDs, and outputs including order details and refund status. Ideal for e-commerce and retail applications requiring secure and auditable order management.

Canonical page: https://skillsregistry.net/skills/techakash32-mcp-order-management-with-rbac  
JSON: https://api.skillsregistry.net/v1/skills/techakash32-mcp-order-management-with-rbac

## Description

Enables role-based order management through MCP tools, allowing users to view and refund orders according to their permissions (USER, MANAGER, ADMIN) with audit logging and JWT authentication handled by a FastAPI client.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/z3zjsu5wdb)
- **Repository:** <https://github.com/techakash32/MCP-Order-Management-with-RBAC>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "techakash32-mcp-order-management-with-rbac"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/techakash32-mcp-order-management-with-rbac` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/techakash32-mcp-order-management-with-rbac/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt