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log-10x

Log10x MCP Server

Official

Dependency check command

log10x_dependency_check
Read-onlyIdempotent

Scan Datadog, Splunk, Grafana, Prometheus, or CloudWatch for alerts, dashboards, or saved searches tied to a log pattern before muting, dropping, or deleting it.

Instructions

Given a pattern identity, generate commands to scan the user's SIEM/observability stack (Datadog monitors, Splunk saved searches, Grafana dashboards, Prometheus alert rules) for anything that depends on that pattern. Call this before any mute, drop, or source-code deletion: deleting a log line that feeds a live alert silently breaks the alert. Also call when a developer asks "am I allowed to delete this log.info() call" or "what references this pattern".

Input Schema

NameRequiredDescriptionDefault
vendorNoSIEM vendor to scan. Omit to auto-detect from ambient credentials (DD_API_KEY+DD_APP_KEY → datadog; SPLUNK_HOST+SPLUNK_TOKEN → splunk; ELASTIC_URL → elasticsearch; AWS chain → cloudwatch). When multiple SIEMs are configured, the tool returns an "ambiguous" error listing them: pass vendor= to disambiguate. When the resolved SIEM has live credentials the scan runs in-process and returns actual dashboard/alert/saved-search names + URLs; otherwise the tool falls back to a paste-ready bash command.
patternYesPattern name (e.g., "Payment_Gateway_Timeout")
serviceNoService name to scope the scan
severityNoSeverity level

Output Schema

NameRequiredDescriptionDefault
dataNo
toolYes
viewNosummary
imagesNo
actionsNo
summaryYes
warningsNo
truncatedNo
next_cursorNo
render_hintNo
generated_atYes
schema_epochYes
schema_versionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.30.8
    • changedInput schema / properties / vendor / description
      Previous value: -"SIEM vendor to scan. Omit to auto-detect from ambient credentials (DD_API_KEY+DD_APP_KEY → datadog; SPLUNK_HOST+SPLUNK_TOKEN → splunk; ELASTIC_URL → elasticsearch; AWS chain → cloudwatch). When multiple SIEMs are configured, the tool returns an \"ambiguous\" error listing them — pass vendor= to disambiguate. When the resolved SIEM has live credentials the scan runs in-process and returns actual dashboard/alert/saved-search names + URLs; otherwise the tool falls back to a paste-ready bash command."New value: +"SIEM vendor to scan. Omit to auto-detect from ambient credentials (DD_API_KEY+DD_APP_KEY → datadog; SPLUNK_HOST+SPLUNK_TOKEN → splunk; ELASTIC_URL → elasticsearch; AWS chain → cloudwatch). When multiple SIEMs are configured, the tool returns an \"ambiguous\" error listing them: pass vendor= to disambiguate. When the resolved SIEM has live credentials the scan runs in-process and returns actual dashboard/alert/saved-search names + URLs; otherwise the tool falls back to a paste-ready bash command."
  2. First observedv1.30.7

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: the consequence of skipping the check (silently breaking a live alert). The credential-dependent in-process vs. bash-command fallback behavior lives in the schema rather than the description, so a higher score is not warranted.

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?

Front-loads purpose, then a bolded imperative warning and additional trigger examples. Every sentence adds decision-relevant information with no filler.

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?

Output schema exists, so return values need not be described, and the schema covers the credential/fallback mechanics. The description says 'generate commands' but the schema reveals it may also run in-process and return live names/URLs; that nuance is not mirrored in the description, though the schema compensates.

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 all four parameters are already documented in the schema. The description only restates the pattern input ('Given a pattern identity') and adds nothing on vendor, service, or severity. Baseline 3 is correct when the schema carries the parameter burden.

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?

States a specific verb (generate commands to scan) plus the resource (SIEM/observability stack dependencies for a given pattern) and enumerates the concrete targets (Datadog monitors, Splunk saved searches, Grafana dashboards, Prometheus alert rules). An agent can distinguish this from sibling tools like log10x_pattern_mitigate without opening either schema.

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?

Gives explicit trigger conditions: call before any mute, drop, or source-code deletion, and call when a developer asks whether a log line is safe to delete or what references a pattern. It names the risk that motivates the call rather than leaving usage to inference.

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