Tool Calling in LLM

• Tool schema: name, description, JSON Schema for args
• LLM returns structured output { "tool": "name", "args": {...} }
• Client executes tool → returns result to LLM
• Parallel tool calls: LLM can invoke multiple tools simultaneously (OpenAI 2023+)
• Model Context Protocol (MCP) — Anthropic 2024 spec for tool standardisation

# OpenAI tool calling
tools = [{
  'type': 'function',
  'function': {
    'name': 'get_weather',
    'description': 'Get current weather',
    'parameters': {
      'type': 'object',
      'properties': {'location': {'type': 'string'}},
      'required': ['location']
    }
  }
}]

response = openai.chat.completions.create(
  model='gpt-5',
  messages=[{'role':'user','content':'Weather in Moscow?'}],
  tools=tools
)
# response.choices[0].message.tool_calls → [{name, arguments}]

• AI Agent
• LLM
• Prompt Injection