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Latent Defense MCP Server

Latent Defense MCP Server

Official
by latent-defense
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

oracle_load_branch

Load an InfraDB branch graph into the oracle session before graph exploration or threat-model matching. For large graphs (1000+ nodes), encoding takes 2-5 minutes; returns immediately, check completion with oracle_graph_info.

Instructions

Load an InfraDB branch graph into the oracle session. Must be called before any graph exploration or threat-model matching.

For large graphs (1000+ nodes), encoding takes 2-5 minutes. This tool returns immediately once encoding has started. Use oracle_graph_info() to check when loading is complete.

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": {
      "branch_id": "<branch_id>"
    },
    "name": "oracle_load_branch"
  }
}

Input Schema

NameRequiredDescriptionDefault
branch_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the asynchronous nature (returns immediately), the encoding delay for large graphs, and the prerequisite ordering. It does not cover potential side effects or error cases, but the core behavioral traits are transparent.

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 two short paragraphs to convey purpose, prerequisites, performance characteristics, and companion tools. Every sentence adds value without redundancy.

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's simplicity (one parameter, async loading), the description covers the essential steps: it must be called before exploration, it returns immediately, and how to monitor completion. The existence of an output schema means return values are documented elsewhere. Minor gaps include missing explanation of where to obtain branch_id.

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?

The input schema has 0% description coverage, so the description must compensate. However, it does not explain the branch_id parameter beyond its name, leaving the agent to infer its meaning (likely from sibling tools like list_branches). This is a significant gap for a single required parameter.

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 the action (load an InfraDB branch graph) and the target (oracle session), and explicitly specifies that it must be called before any graph exploration or threat-model matching. This distinguishes it from sibling tools like oracle_load_status and oracle_graph_info, which serve related but distinct purposes.

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

Usage Guidelines4/5

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

The description provides clear guidance on when to use the tool (before exploration or threat-model matching) and mentions the asynchronous behavior for large graphs, including expected encoding time and how to check completion via oracle_graph_info. It could be improved by explicitly stating when not to use it (e.g., if already loaded), but the current guidance is effective.

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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