aethershell 0.3.1

The world's first multi-agent shell with typed functional pipelines and multi-modal AI
Documentation 
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# Example 14: AI Backends + MCP Server Integration
# Demonstrates using auto-detected AI backends with MCP servers for agent tool use

print("=== AI + MCP Integration Demo ===")
print("")

# Part 1: Detect AI Backends
print("1. AI Backend Detection:")
let backends = ai_backends()
let selected_backend = ai_detect()
print("   Available backends: " + len(backends))
print("   Auto-selected: " + selected_backend)
print("")

# Part 2: Detect MCP Servers  
print("2. MCP Server Detection:")
let mcp_servers = mcp_servers()
print("   Available MCP servers: " + len(mcp_servers))
print("")

# Part 3: Show what's available
print("3. Integration Capabilities:")
print("")
print("   AI Backends: Ready")
print("   MCP Servers: Detection ready")
print("   Common MCP ports: 3001-3005, 8080-8081")
print("")

# Part 4: Usage Examples
print("4. Usage Patterns:")
print("")
print("   A. Simple AI query with auto-detected backend:")
print("      let response = ai(ai_detect(), \"What is 2+2?\")")
print("")
print("   B. Agent with AI backend (no tools):")
print("      let simple_agent = agent(")
print("        \"Answer questions\",")
print("        ai_detect(),")
print("        []")
print("      )")
print("")
print("   C. Agent with AI backend + MCP tools:")
print("      let fs_server = mcp_detect(\"http://localhost:3001\")")
print("      let agent_with_tools = agent(")
print("        \"File analyzer\",")
print("        ai_detect(),")
print("        [")
print("          {tool: \"read_file\", server: fs_server.endpoint},")
print("          {tool: \"list_dir\", server: fs_server.endpoint}")
print("        ]")
print("      )")
print("")
print("   D. Multi-backend agent swarm:")
print("      let agents = [")
print("        {id: \"fast\", model: \"ollama:llama3.2:3b\"},")
print("        {id: \"smart\", model: \"ollama:llama3.1:70b\"},")
print("        {id: \"cloud\", model: \"openai:gpt-4o\"}")
print("      ]")
print("")

# Part 5: Getting Started
print("5. Getting Started:")
print("")
print("   Step 1: Start an MCP server")
print("     python mcp_server.py --port 3001")
print("")
print("   Step 2: Detect it")
print("     let server = mcp_detect(\"http://localhost:3001\")")
print("")
print("   Step 3: Use it with an AI agent")
print("     agent(\"goal\", ai_detect(), server.tools)")
print("")

print("✓ AI + MCP integration ready!")
print("")
print("Next steps:")
print("  - Start MCP servers for tool access")
print("  - Use ai_detect() for automatic backend selection")
print("  - Combine both for powerful AI agents with tools")