CLI and MCP server for Applied Labs AI support agents
Project description
Applied Labs CLI
CLI and Claude Code plugin for managing Applied Labs AI support agents.
Installation
As a Claude Code Plugin
# From a marketplace (once published)
/plugin install applied-labs@marketplace-name
# Or test locally
claude --plugin-dir /path/to/applied-cli
As a standalone CLI
pip install applied-cli
# Or with MCP server support
pip install "applied-cli[mcp]"
Authentication
applied-cli auth login # Opens browser for approval
applied-cli auth status # Check current shop
applied-cli auth shops # List available shops
applied-cli auth use-shop NAME # Switch shops
Quick Start
1. Set up a new shop
# Generate spec template
applied-cli shop template > my-shop.yaml
# Edit the spec with your configuration...
# Run setup
applied-cli shop setup --spec my-shop.yaml --json
2. Test your agent
applied-cli chat --agent-id <uuid> --message "Hello"
3. Fix failing scenarios
# Get context for failures
applied-cli test fix context --benchmark-id <uuid> --json
# Update knowledge base
applied-cli knowledge upsert --agent-id <uuid> --type qa \
--question "What is your return policy?" \
--answer "30 day returns on all items."
# Batch test fixes
applied-cli test fix batch --source <failing-benchmark> --target <validation-benchmark>
# Check progress
applied-cli test fix status --source <source> --target <target>
Command Reference
applied-cli
├── auth # Login, logout, switch shops
├── shop # Bootstrap new shops from YAML spec
├── agent # List, create, update agents
├── chat # Send a message to an agent
├── conversations # List, show, import conversations
├── insights # Generate analytics reports
├── knowledge # Q&A entries, escalation rules
├── taxonomy # Topic/intent classification
├── test # Testing workflows
│ ├── benchmarks # Scenario collections
│ ├── scenarios # Individual test cases (includes rate)
│ ├── runs # Execution records
│ ├── coverage # Coverage summaries
│ └── fix # Fix failing scenarios
└── simulate # Generate test conversations
MCP Server
The CLI includes an MCP server for Claude integrations:
# Run directly (after pip install)
applied-cli-mcp
# Or via uvx (after publishing to PyPI)
uvx --from "applied-cli[mcp]" applied-cli-mcp
Claude Desktop Configuration
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"applied-labs": {
"command": "applied-cli-mcp"
}
}
}
Plugin Skills
When installed as a Claude Code plugin, these skills are available:
/applied-labs:setup-shop- Guided shop setup workflow/applied-labs:fix-scenarios- Fix failing test scenarios
Environment Variables
| Variable | Description |
|---|---|
APPLIED_ENDPOINT |
prod, dev, local, or full URL |
APPLIED_SHOP_ID |
Pre-select shop UUID |
APPLIED_API_TOKEN |
Skip browser auth |
APPLIED_PROFILE |
Named credential profile |
Development
# Install in development mode
pip install -e ".[mcp]"
# Test CLI
applied-cli --help
# Test MCP server
applied-cli-mcp
# Test as Claude Code plugin
claude --plugin-dir .
License
MIT
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