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mcp-sumologic

mcp-sumologic

by giftHEALTH
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

search_logs

Execute Sumo Logic log searches to retrieve raw messages. Designed for non-aggregation queries.

Instructions

Run a Sumo Logic log search and return raw messages. Use for non-aggregation queries.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_logs"
  }
}

Input Schema

NameRequiredDescriptionDefault
toNo
fromNo
limitNo
queryYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries full behavioral disclosure burden. It states the tool returns 'raw messages', which is a basic behavioral trait but lacks details on pagination, error handling, or authentication. It is adequate but not thorough.

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 extremely concise with two sentences: one stating the action and output, another for usage guidance. There is no unnecessary text.

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

Completeness2/5

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

With 4 parameters, no output schema, and no annotations, the description is too brief. It fails to explain parameter formats (e.g., timestamps for from/to), query syntax, pagination, or response structure, leaving significant gaps for an agent.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate. However, it does not explain the meaning of any parameter (query, from, to, limit), leaving the agent without guidance on format or usage beyond the schema's type definitions.

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 'Run a Sumo Logic log search and return raw messages' with a specific verb and resource. It distinguishes from siblings by specifying 'Use for non-aggregation queries', contrasting with the sibling tool search_aggregate.

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 explicitly says 'Use for non-aggregation queries', providing clear context for when to use this tool. It implicitly suggests not to use it for aggregation, and the sibling list includes search_aggregate, so an agent can infer the alternative.

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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