This document outlines the specification for tools within the Logging & Monitoring module that are intended to be integrated with the Model Context Protocol (MCP).
The Logging & Monitoring module, as currently designed, provides core logging functionalities (setup_logging(), get_logger()) for internal use by other Codomyrmex modules. These functions are primarily for programmatic integration within the application lifecycle and are not suited for exposure as Model Context Protocol (MCP) tools.
MCP tools are typically designed for discrete, invocable actions or queries that an external agent (like an LLM) would trigger. The internal logging mechanisms do not fit this paradigm.
If future enhancements to this module introduce features that are appropriate for MCP (e.g., a tool to dynamically query specific log entries, or to change log levels at runtime via an external command), this document will be updated accordingly.
For details on how to use the logging functionalities within your Python code, please refer to the module's README.md and API_SPECIFICATION.md.
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- Module Index: All Agents
- Documentation: Reference Guides
- Home: Root README
- Strict Modularity: Each component is isolated and communicates via well-defined APIs.
- Performance Optimization: Implementation leverages lazy loading and intelligent caching to minimize resource overhead.
- Error Resilience: Robust exception handling ensures system stability even under unexpected conditions.
- Extensibility: The architecture is designed to accommodate future enhancements without breaking existing contracts.
The codebase utilizes modern Python features (version 3.10+) to provide a clean, type-safe API. Interaction patterns are documented in the corresponding AGENTS.md and SPEC.md files, ensuring that both human developers and automated agents can effectively utilize these capabilities.