store-mcp-connect

Connect AI Agent to Your Store (MCP)

Connect your AI coding agent to your Mobazha store via MCP (Model Context Protocol). Once connected, your agent can directly manage products, orders, messages, and more.

What You Get

After connecting, your AI agent has access to 30+ store management tools:

Category	Tools	What They Do
Products	listings_create, listings_update, listings_delete, listings_list_mine, listings_import_json	Full product CRUD + bulk import
Orders	orders_get_sales, orders_confirm, orders_fulfill, orders_refund	Order lifecycle
Chat	chat_get_conversations, chat_send_message	Buyer communication
Discounts	discounts_create, discounts_update, discounts_delete	Promotions
Collections	collections_create, collections_add_products	Product organization
Profile	profile_get, profile_update	Store identity
Notifications	notifications_list, notifications_mark_read	Activity feed
Search	search_listings, search_profiles	Marketplace discovery
Finance	exchange_rates_get, wallet_get_receiving_accounts, fiat_get_providers	Payments and rates

Connection Method: SSE (Recommended)

All Mobazha deployments include a built-in MCP SSE endpoint. This is the recommended method because:

• No additional binary to install or maintain
• Tools are always up-to-date with your store version
• Works with Claude Code, Cursor, Codex, and all modern AI agents

SSE Endpoint

Deployment	SSE URL
SaaS	https://app.mobazha.org/platform/v1/mcp/sse
Standalone (custom domain)	https://shop.example.com/platform/v1/mcp/sse
Standalone (local Docker)	http://localhost/platform/v1/mcp/sse
Native install (local)	http://localhost:5102/platform/v1/mcp/sse
Native install (VPS)	http://<vps-ip>:5102/platform/v1/mcp/sse

---

Step 1: Get Your API Token

SaaS Store

1. Log in to your store at app.mobazha.org
2. Go to Settings > API
3. Click Generate Token
4. Copy the token

Standalone Store (Docker with domain)

Open your store's admin panel in a browser and generate a token via Settings > API, or via curl:

curl -X POST https://shop.example.com/platform/v1/auth/tokens \
  -H "Content-Type: application/json" \
  -d '{"username": "admin", "password": "<your-admin-password>"}'

Native Install (local or VPS)

The default gateway port for native installs is 5102:

curl -X POST http://localhost:5102/platform/v1/auth/tokens \
  -H "Content-Type: application/json" \
  -d '{"username": "admin", "password": "<your-admin-password>"}'

For a VPS, replace localhost with your server's IP or use an SSH tunnel:

ssh -L 5102:localhost:5102 root@<vps-ip>
# Then use http://localhost:5102 from your local machine

---

Step 2: Configure Your AI Agent

Claude Code

Add to ~/.claude.json (or project-level .mcp.json):

{
  "mcpServers": {
    "mobazha-store": {
      "type": "sse",
      "url": "https://shop.example.com/platform/v1/mcp/sse",
      "headers": {
        "Authorization": "Bearer <your-token>"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "mobazha-store": {
      "url": "https://shop.example.com/platform/v1/mcp/sse",
      "headers": {
        "Authorization": "Bearer <your-token>"
      }
    }
  }
}

Or go to Settings > MCP Servers > Add Server and enter the SSE URL.

Codex CLI

codex mcp add mobazha-store --transport sse \
  --url "https://shop.example.com/platform/v1/mcp/sse" \
  --header "Authorization: Bearer <your-token>"

OpenCode

Add to opencode.json:

{
  "mcp": {
    "mobazha-store": {
      "type": "sse",
      "url": "https://shop.example.com/platform/v1/mcp/sse",
      "headers": {
        "Authorization": "Bearer <your-token>"
      }
    }
  }
}

Replace https://shop.example.com with your actual store URL from the table above.

---

Step 3: Verify the Connection

Ask your AI agent:

"List my store's products" or "Show my recent orders"

The agent should call listings_list_mine or orders_get_sales and return results. If it works, the connection is live.

For a guide on what you can do with MCP tools, see the store-management skill.

---

Advanced: stdio Transport

For environments where SSE is not supported by the AI agent, or for air-gapped setups, a mobazha-mcp stdio binary is available. It ships with the standalone Docker image and native install.

When to Use stdio

• Your AI agent doesn't support SSE MCP transport
• Air-gapped or restricted network environment
• Development/debugging of the MCP layer itself

Using stdio from Standalone Docker

The binary is bundled in the container:

docker exec -it <container> mobazha-mcp --gateway-url http://localhost:5102 --token <token>

stdio CLI Reference

Flag	Env Variable	Default	Description
--gateway-url	MOBAZHA_GATEWAY_URL	http://localhost:5102	Store gateway URL
--token	MOBAZHA_TOKEN	(required)	Bearer token
--search-url	MOBAZHA_SEARCH_URL	(optional)	Marketplace search API URL

stdio Agent Configuration

{
  "mcpServers": {
    "mobazha-store": {
      "command": "mobazha-mcp",
      "args": ["--gateway-url", "http://localhost:5102"],
      "env": {
        "MOBAZHA_TOKEN": "<your-token>"
      }
    }
  }
}

---

Troubleshooting

"connection refused" or timeout

• Native install: verify the store is running with curl http://localhost:5102/healthz
• Standalone Docker: the SSE endpoint is at port 80/443 (not 5102), try curl http://localhost/healthz
• For remote stores, check that the domain resolves and HTTPS is configured

"401 Unauthorized"

• Verify the token: curl -H "Authorization: Bearer <token>" http://localhost:5102/v1/profiles
• Token may have expired — generate a new one
• Ensure the token has the required scopes for the tools you want to use

"tool not found"

• search_listings and search_profiles require the marketplace search service
• Some tools require specific scopes on the API token (e.g., listings:write for listings_create)

Credential Safety

• Store the token in environment variables, not in config files committed to git
• Add MCP config files to .gitignore if they contain tokens
• Tokens can be revoked and regenerated at any time