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splunk-mcp-server

splunk-mcp-server

by balajifunny
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_knowledge_objects

Retrieve Splunk knowledge objects such as saved searches, lookups, and macros by specifying their type.

Instructions

Get knowledge objects from Splunk. Supported types include saved_searches, lookups, macros, etc.

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": {
      "type": "<type>"
    },
    "name": "get_knowledge_objects"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeYes
countNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.8/5.0
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It does not mention that the tool is read-only, any side effects, or limitations. The description is too brief to convey transparency.

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, using only two sentences that front-load the main purpose. Every sentence adds value with no redundancy.

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?

Given the absence of an output schema and annotations, the description is incomplete. It does not explain the return value format, any restrictions on the 'type' parameter, or how pagination works with 'count'.

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

Parameters2/5

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

With 0% schema description coverage, the description should compensate. It only gives examples for the 'type' parameter and does not explain the 'count' parameter's meaning or behavior. This leaves ambiguity for the agent.

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?

The description clearly states the action ('Get knowledge objects from Splunk') and the resource, supported by examples of types. It distinguishes from siblings like search_splunk and get_user_info by specifying a distinct resource category.

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?

No guidance on when to use this tool versus alternatives. It does not mention when not to use it or direct users to sibling tools for other purposes.

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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