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Python SDK for tool usage logging and monitoring

Project description

Observe Python SDK

A Python SDK for tool 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

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

@observee_usage_logger
async def your_function():
    # Your 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")

Per-Decorator Configuration

from observee import ObserveeConfig, observee_usage_logger

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

Features

  • Tool usage logging with async support
  • Automatic logging of:
    • Tool name
    • Input parameters
    • Response data
    • Execution duration
    • Error information (if any)
  • Configurable logging endpoint (defaults to Observe API)
  • Error handling and reporting
  • Performance tracking
  • Flexible MCP server name configuration
  • Enterprise API key support for enhanced features

Logging Details

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
  • API key (for enterprise customers only)

Logs are sent asynchronously to avoid impacting tool performance.

Requirements

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

License

MIT

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