Skip to main content
Glama
parajiholkar

Multi-Container Log Correlator MCP Server

by parajiholkar

Search by Trace ID

search_by_trace_id
Read-onlyIdempotent

Search all container logs by trace ID to produce a chronological merged timeline of every service event, helping isolate cascading failures.

Instructions

Return a chronologically merged timeline of all log events across every container that share a specific trace / request ID.

This is the primary debugging tool. It correlates distributed transactions in O(1) time using the in-memory trace index.

Args:

  • trace_id (string): The correlation ID to search for (e.g. "req-998877", a W3C traceparent trace hex).

  • limit (number, 1-500): Maximum events to return. Default 200.

Returns: A chronological list of log lines across all services tagged with this trace_id, showing the full distributed call path — ideal for pinpointing cascading failures.

Example: search_by_trace_id({ trace_id: "req-998877" })

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of log events to return (default 200).
trace_idYesThe trace/request/correlation identifier to search for (e.g. 'req-998877', a W3C traceparent hex ID).

Schema Changelog

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

  1. First observedv1.0.0

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable behavioral context by explaining the chronological merging across all containers, the O(1) in-memory trace index, and the return of the full distributed call path. This goes well beyond the annotations and helps the agent understand expected behavior and performance.

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

Conciseness5/5

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

The description is well-organized with a front-loaded purpose sentence, followed by context, parameters, return value, and an example. Each section earns its place and there is no redundant filler. The information is dense but scannable.

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?

Although there is no output schema, the description explicitly explains the return value as a chronological list of log lines across all services showing the distributed call path. It also states parameter constraints, defaults, and provides an example invocation. For a two-parameter read-only tool with full schema coverage, this is complete.

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?

Schema description coverage is 100%, so the schema already fully documents both parameters. The Arg descriptions in the tool description largely duplicate the schema, with the only added value being a concrete example call and the embedded format examples for trace_id. Since the schema carries the semantic load, a baseline score of 3 is appropriate.

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 opens with a specific verb and resource: 'Return a chronologically merged timeline of all log events across every container that share a specific trace / request ID.' This clearly states what the tool does and the scope. It also positions itself as 'the primary debugging tool,' which helps distinguish it from more generic siblings like search_logs.

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 phrase 'This is the primary debugging tool' provides clear context for when to use it, and the emphasis on correlating distributed transactions signals its intended use case. However, it does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/parajiholkar/multi-container-log-correlator-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server