Adobe Commerce Support MCP Server
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Adobe Commerce Support MCP Server
This MCP server helps generate professional Adobe Commerce support responses from case findings.
Installation
Dependencies are already installed ✅
Server is ready to use ✅
Related MCP server: Magento MCP Server
Usage with Cursor
To use this MCP server with Cursor, add the following configuration to your Cursor settings:
Option 1: Add to Cursor Settings (Recommended)
Open Cursor Settings (Cmd+,)
Search for "MCP"
Add this server configuration:
{
"mcpServers": {
"adobe-support-mcp": {
"command": "python3",
"args": ["/Users/kavingas/VSCodeProjects/mcp_support_server/mcp_support_server.py"],
"env": {}
}
}
}Option 2: Use the provided config file
The mcp_config.json file in this directory contains the ready-to-use configuration.
How to Use
Option 1: Structured Content (Traditional)
Create a
find.mdfile with properly structured content:
### Findings
[Your investigation findings here]
### Analysis
[Your technical analysis here]
### Recommendations
[Your recommended solutions here]Use the
generate_support_replytool to create a professional customer response.
Option 2: Mixed Content (New - LLM Assisted)
Create a
find.mdfile with mixed/unstructured content (any format)Use either:
categorize_mixed_contenttool first, then use LLM to process the categorization promptgenerate_support_replywithauto_categorize=true(default) for automatic handling
The server will automatically detect if your content needs categorization and provide LLM prompts to organize it properly.
Tools Available
generate_support_reply: Generates a professional Adobe Commerce support response from case findings
find_file: Input file (default: "find.md")resp_file: Output file (default: "resp.md")auto_categorize: Automatically handle mixed content (default: true)
categorize_mixed_content: Creates LLM prompts to categorize mixed content into structured format
find_file: Input file with mixed content (default: "find.md")categorized_file: Output file with categorization prompt (default: "categorized.md")
Files
mcp_support_server.py- Main MCP serverrequirements.txt- Python dependenciesmcp_config.json- Cursor configurationsetup.py- Installation script
Tool Schema Changelog
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This server cannot be deployed
Maintenance
Related MCP Connectors
Review support tickets, send approved replies, and manage supported ProxyAI Agent Tasks.
Paste a transcript or document and get a structured summary with action items, plus slides and repor
Ask questions about your support tickets, chats, agents and AI answer quality, with cited tickets.
Draft cited RFP and security questionnaire answers from your knowledge base, with human review
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