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Latent Defense MCP Server

Latent Defense MCP Server

Official
by latent-defense
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

search_nodes

Search nodes in a GitHub repository using a text query to locate relevant infrastructure graph elements.

Instructions

Search nodes in a repository by text query.

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": {
      "repo_id": "<repo_id>",
      "query": "<query>"
    },
    "name": "search_nodes"
  }
}

Input Schema

NameRequiredDescriptionDefault
repo_idYes
queryYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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 does not disclose behavioral traits such as read-only nature, search scope, pagination, or error handling. The description is too minimal to inform the agent of side effects or constraints.

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?

The description is a single sentence, concise and front-loaded. However, it could include more helpful information without becoming verbose.

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 presence of an output schema, the description does not need to explain return values. However, the tool has two required parameters and no annotations, and the description fails to mention search behavior (e.g., case sensitivity, exact match vs fuzzy) or limitations, leaving the agent under-informed.

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?

Schema coverage is 0%, and the description adds only that 'query' is a text query. It does not specify format, allowed characters, or max length for either parameter. The description adds marginal semantic value beyond the parameter names.

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 (search), resource (nodes), and context (in a repository by text query). It distinguishes 'search_nodes' from siblings like 'oracle_search_nodes' by implying it's a general search, but doesn't explicitly differentiate.

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 (e.g., oracle_search_nodes). No prerequisites or exclusions are mentioned, leaving the agent to infer from the schema.

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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