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sumo-mcp

by droyad
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JavaScript
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sumo-mcp

Sumo Logic用のsearch_logsツールを1つ公開する最小限のMCPサーバーです。

ビルド

npm install
npm run build

Related MCP server: Graylog MCP Server

Claude Codeでの設定

APIキー

Sumoでの操作:

  • ユーザー名をクリックし、Personal Access Keysを選択します

  • Add New Access Keyをクリックします

  • 名前（例: Claude Local）を入力します

  • スコープの下にあるCustomを選択します

  • Log Searchセクションの下にあるRun Log Searchにチェックを入れます

  • キーを保存します

インストール

claude mcp add --scope user sumo `
  --env SUMO_ACCESS_ID=<your-access-id> `
  --env SUMO_ACCESS_KEY=<your-access-key> `
  --env SUMO_ENDPOINT=https://api.us2.sumologic.com `
  -- node C:\Source\SumoMcp\dist\index.js

SUMO_ENDPOINTはhttps://api.*.sumologic.comと一致する必要があります。Sumoデプロイメントリージョン（US2、EU、AUなど）のホストを選択してください。

ツール

search_logs(query, from?, to?, max_results?, timezone?)

  • query — Sumo検索式

  • from / to — ISO 8601またはSumo相対時間（-15m、-1h、now）。デフォルトは-15m / now

  • max_results — デフォルトは100、上限は1000

  • timezone — IANA名、デフォルトはUTC

_messageTime、_sourceCategory、_sourceHost、_sourceName、_rawを含むメッセージのJSON配列を返します。

ハードタイムアウトは60秒です。タイムアウトが発生した場合は、時間範囲を狭めるか、クエリを調整してください。

設計

docs/superpowers/specs/2026-05-07-sumo-mcp-design.mdを参照してください。

Available Tools

1 tool
search_logsA

Run a Sumo Logic search and return matching log lines. Use this to investigate production issues, find errors, trace events, or look up activity in logs. Returns trimmed messages with timestamp, source category, host, source name, and raw log line.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesSumo Logic search expression (e.g. `_sourceCategory=prod/api error`).
fromNoStart time. ISO 8601 (e.g. "2026-05-07T10:00:00") or Sumo relative ("-15m", "-1h", "-1d", "now"). Default "-15m".
toNoEnd time. Same format as `from`. Default "now".
max_resultsNoMax messages to return. Default 100, capped at 1000.
timezoneNoIANA timezone name for the search (e.g. "UTC", "Europe/London"). Default "UTC".

TDQS

A4.4/5.0
Behavior4/5

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

The description discloses the return format: 'Returns trimmed messages with timestamp, source category, host, source name, and raw log line.' Since no annotations exist, the description sufficiently informs about the tool's read-only nature and output structure.

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, consisting of only two sentences. The first sentence states the core function, and the second provides use cases and return fields. No redundant information.

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?

Given the tool has 5 parameters and no output schema, the description covers the purpose, usage timing, and return structure. It is sufficiently complete for an agent to understand when and how to use it.

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 coverage is 100%, with each parameter described. The tool description does not add extra semantic detail beyond the schema; however, the schema descriptions are adequate. Baseline 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 clearly states 'Run a Sumo Logic search and return matching log lines', specifying the exact action and resource. It also lists specific use cases like investigating production issues, finding errors, and tracing events.

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

Usage Guidelines5/5

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

The description explicitly states when to use the tool: 'Use this to investigate production issues, find errors, trace events, or look up activity in logs.' This provides clear context for usage.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool updatev0.1.0
    • First observedsearch_logs
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no potential for ambiguity. The single tool is clearly defined and cannot be confused with any other.

Naming Consistency5/5

The single tool name 'search_logs' follows a clear verb_noun pattern, which is consistent and predictable.

Tool Count2/5

A single tool for a logging platform seems insufficient. Typical users would expect additional tools for managing searches, retrieving past results, or listing sources, making the count feel too limited for the domain.

Completeness2/5

The server only offers a search functionality without supporting operations like listing saved searches, polling search status, or retrieving historical results. This leaves significant gaps for a complete log investigation workflow.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

Related MCP Connectors

Related MCP Servers

  • MCP Sumo Logic Server

    samwang0723
    F
    license
    Not graded
    quality
    D
    maintenance
    Integrates with Sumo Logic's API to enable log search with configurable queries and time ranges, supporting error handling and easy deployment via Docker.
    6 npm
    11
    -

  • Graylog MCP Server

    PrinceGupta1999
    A
    license
    Not graded
    quality
    C
    maintenance
    Enables AI assistants to query and analyze logs from Graylog instances using universal search with relative or absolute time windows, supporting both full result retrieval and lightweight count-only queries.
    10 npm
    1
    MIT