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nks1097

Splunk Enterprise MCP Server

by nks1097

splunk_detect_brute_force

Detects potential brute force attacks or credential stuffing by analyzing repeated failed login attempts within a configurable time window and threshold.

Instructions

Detect potential brute force attacks or credential stuffing based on repeated failed logins.

Args: threshold: Minimum failed attempts to flag (default 5). time_window: Bin duration (default '15m'). earliest_time: Time range to analyze (default '-4h').

Input Schema

NameRequiredDescriptionDefault
thresholdNo
time_windowNo15m
earliest_timeNo-4h

Output Schema

NameRequiredDescriptionDefault
dataNoOutput payload or results
errorNoError message if execution failed
successNoWhether the tool execution succeeded
metadataNoExecution timing, pagination and environment details
warningsNoOperational warnings or notices
request_idNoCorrelation ID for audit trail and observability

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses the detection logic (thresholding repeated failures over a binned window), but never states that this is a read-only analysis, what the grouping dimension is (per user, per IP, per host), or how expensive the underlying search is.

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?

One-sentence purpose followed by a compact Args block with defaults; no filler and the objective is front-loaded. The Args list is functional but thin relative to the schema it mirrors.

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

Completeness3/5

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

An output schema exists, so return values need not be described. Still, for a security detection tool with zero annotations, the definition omits the detection scope (which log sources/fields, group-by key) and whether the agent can expect distinct entities or raw bins.

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

Parameters4/5

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

Schema description coverage is 0%, yet the description documents all three parameters with defaults and intent, which compensates well. It is slightly weaker on 'time_window: Bin duration', which doesn't clarify the accepted format or what the bin is grouped by.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and detection objective ('Detect potential brute force attacks or credential stuffing based on repeated failed logins'), which is clear enough to act on. It does not, however, differentiate itself from the sibling splunk_detect_failed_logins, which sounds like an adjacent/overlapping tool.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this versus splunk_detect_failed_logins, splunk_investigate_ip, or the general search tools. The only implicit cue is 'repeated failed logins,' which leaves the agent to infer the aggregation/threshold distinction on its own.

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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