observee 0.1.7

Python SDK for tool usage logging and monitoring

Observe Python SDK

A Python SDK for tool and prompt usage logging and monitoring.

Installation

pip install observee

Usage

You can set the MCP server name either globally or per decorator:

Global Configuration

from observee import ObserveeConfig, observee_usage_logger, observee_prompt_logger

# Set the MCP server name globally
ObserveeConfig.set_mcp_server_name("your-mcp-server-name")

@observee_usage_logger
async def your_tool_function():
    # Your tool code here
    pass

@observee_prompt_logger
async def your_prompt_function():
    # Your prompt code here
    pass

API Key Configuration (Enterprise Customers Only)

from observee import ObserveeConfig

# Set your enterprise API key
ObserveeConfig.set_api_key("your-enterprise-api-key")

Tool Usage Logging

from observee import ObserveeConfig, observee_usage_logger

@observee_usage_logger
async def your_tool_function():
    # Your tool code here
    pass

Prompt Usage Logging

from observee import ObserveeConfig, observee_prompt_logger

@observee_prompt_logger
async def your_prompt_function():
    # Your prompt code here
    pass

Features

• Tool and prompt usage logging with async support
• Automatic logging of:
  • Tool/prompt name
  • Input parameters
  • Response data
  • Execution duration (for tools)
  • Error information (if any)
• Configurable logging endpoint (defaults to Observe API)
• Error handling and reporting
• Performance tracking (for tools)
• Flexible MCP server name configuration
• Enterprise API key support for enhanced features
• Privacy protection: Input/response data only logged when API key is provided

Logging Details

Tool Usage Logging

The SDK automatically logs the following information for each tool usage:

• MCP server name
• Tool name (derived from function name)
• Tool input parameters (as JSON)
• Tool response
• Execution duration in milliseconds
• Any errors that occur during execution

Prompt Usage Logging

The SDK automatically logs the following information for each prompt usage:

• MCP server name
• Prompt name (derived from function name)
• Prompt input parameters (as JSON)
• Prompt response
• Any errors that occur during execution

Privacy Protection

For privacy protection, detailed input and response data is only logged when an enterprise API key is configured. Without an API key, only basic metadata (server name, tool/prompt name, duration) is logged.

Logs are sent asynchronously to avoid impacting tool/prompt performance.

Requirements

• Python 3.8 or higher
• Dependencies:
  • httpx
  • pydantic

License

MIT