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parajiholkar

Multi-Container Log Correlator MCP Server

by parajiholkar

Search Logs

search_logs
Read-onlyIdempotent

Search container logs by substring to find error messages, stack traces, or any freeform text across all services or a specific container. Filter by log level and limit results.

Instructions

Full-text search across all (or a specific) container's buffered log lines.

Useful for finding specific error messages, stack trace snippets, SQL queries, or any freeform string that doesn't have a structured trace ID.

Args:

  • query (string): Case-insensitive substring to search for in log messages.

  • service_name (string, optional): Restrict search to this container. Omit to search all.

  • limit (number, 1-500): Max matching lines to return. Default 100.

  • level_filter (string[], optional): Restrict to specific log levels.

Returns: Matching log lines in chronological order with their service name, timestamp, and level.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of matching lines to return (default 100).
queryYesCase-insensitive substring or simple pattern to search in log messages.
level_filterNoRestrict results to these log levels.
service_nameNoRestrict search to this container/service. Omit to search all containers.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful behavioral context beyond that: it searches buffered lines, returns results in chronological order, and specifies the returned fields. It does not mention rate limits or buffer retention, but these are not critical for a read-only search tool.

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?

Purpose is front-loaded and the description is compact, with a useful use-case sentence and a clear return-value sentence. The Args block is somewhat redundant with the schema, but it is well organized and easy to scan.

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

Completeness5/5

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

With no output schema, the description explicitly covers the return shape: chronological log lines with service name, timestamp, and level. It also covers scope, optional service restriction, level filtering, limit behavior, and the intended use case, making it sufficient for correct tool selection and invocation.

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

Parameters3/5

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

The input schema provides 100% parameter coverage with clear descriptions, so the schema already explains every parameter and constraint. The Args section restates the same meanings without adding new semantic information, which meets the baseline but does not exceed it.

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 first sentence states a specific action (full-text search) and resource (container's buffered log lines) with an explicit optional scope. It also distinguishes itself from structured trace-ID lookup by emphasizing freeform strings, so an agent can tell it apart from search_by_trace_id.

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

Usage Guidelines4/5

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

The description gives a clear use case: finding error messages, stack traces, SQL queries, or freeform strings without a structured trace ID. This implies when to prefer this tool over structured-ID search, though it does not explicitly name sibling alternatives or state exclusion conditions.

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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