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Fato07

Log Analyzer MCP

by Fato07
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

log_analyzer_parse

Read-onlyIdempotent

Parse and analyze log files by automatically detecting format and extracting metadata including time range and level distribution. Supports nine log formats with optional hints, line limits, and markdown or JSON output.

Instructions

Parse and analyze a log file, detecting its format and extracting metadata.

Args:
    file_path: Path to the log file to analyze
    format_hint: Force specific format (syslog, apache_access, apache_error, jsonl,
                 docker, python, java, kubernetes, generic) or None for auto-detect
    max_lines: Maximum lines to parse (100-100000, default 10000)
    response_format: Output format - 'markdown' or 'json'

Returns:
    Analysis results including detected format, time range, level distribution,
    and sample entries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
format_hintNo
max_linesNo
response_formatNomarkdown

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Tool Definition Quality

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations indicate read-only, idempotent behavior. Description adds what the tool returns (detected format, time range, level distribution, sample entries), providing good behavioral context. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Structured as a docstring with overview and parameter list. Front-loaded with purpose. Slightly verbose but efficient for the information needed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers main functionality and parameters. Output schema exists so return details are sufficient. Missing error conditions or file prerequisites, but overall comprehensive.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description fully explains each parameter: file_path, format_hint (with list of values), max_lines (with range), response_format. This compensates entirely.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it parses and analyzes log files, detecting format and extracting metadata. This separates it from sibling tools like search, summarize, etc.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for initial log parsing but lacks explicit guidance on when to use alternatives or when not to use. Sibling tools provide context but no direct exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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