From mcp-companion
Downloads Qlerify data such as workflows, OpenAPI specs, entities, and domain events to local JSON/YAML files via curl + jq. Bypasses slow AI-processed MCP tools for 100x faster large exports.
How this skill is triggered — by the user, by Claude, or both
Slash command
/mcp-companion:downloadThis skill is limited to the following tools:
The summary Claude sees in its skill listing — used to decide when to auto-load this skill
**CRITICAL:** When saving ANY Qlerify data to a file, use `curl + jq` instead of MCP tools. MCP responses pass through
CRITICAL: When saving ANY Qlerify data to a file, use curl + jq instead of MCP tools. MCP responses pass through
AI context which takes minutes for large data. Shell pipes take seconds.
cat ~/.claude.json 2>/dev/null | jq -r '.mcpServers.qlerify // empty'
Extract the url and headers.x-api-key.
curl -s "$MCP_URL" \
-H "x-api-key: $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "TOOL_NAME",
"arguments": { ...ARGS... }
}
}' | jq -r '.result.content[0].text | fromjson' > output.json
curl -s "$MCP_URL" -H "x-api-key: $API_KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_workflow","arguments":{"workflowId":"...","projectId":"..."}}}' \
| jq -r '.result.content[0].text | fromjson | .specification' > workflow.json
curl -s "$MCP_URL" -H "x-api-key: $API_KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"generate_openapi_spec","arguments":{"workflowId":"...","projectId":"...","boundedContext":"..."}}}' \
| jq -r '.result.content[0].text' > swagger.yaml
curl -s "$MCP_URL" -H "x-api-key: $API_KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_workflow","arguments":{"workflowId":"...","projectId":"..."}}}' \
| jq -r '.result.content[0].text | fromjson | .specification.schemas.entities' > entities.json
curl -s "$MCP_URL" -H "x-api-key: $API_KEY" -H "Content-Type: application/json" \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_workflow","arguments":{"workflowId":"...","projectId":"..."}}}' \
| jq -r '.result.content[0].text | fromjson | .specification.domainEvents' > events.json
| Data size | Method | Example |
|---|---|---|
| Small (< 50 lines) | MCP tool | list_workflows |
| Large (> 50 lines) | curl + jq | get_workflow, generate_openapi_spec |
| Any "save to file" | curl + jq | Always, regardless of size |
Use MCP tools for small lookups:
list_workflows → get workflow ID and project IDThen use curl for the actual data fetch.
npx claudepluginhub qlerify/qlerify-plugins --plugin mcp-companionDefines the shared routing ladder, result presentation contract, filesystem safety rules, and Tier 1-to-Tier 3 fallback policy for Retriever tasks.
Generates Dify workflow DSL files (YAML/JSON) from natural language descriptions, with correct node schemas, edges, and layout for direct import.
Creates, runs, monitors, manages, and reviews Conductor workflows including agentic workflows with LLM, MCP, and RAG. Use when defining workflows, building AI agents, or managing executions.