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vectra-ai-research

Vectra AI MCP Server

list_entities

Retrieve detailed information about hosts and accounts in the Vectra AI platform using filters like entity type, state, priority, and tags to analyze security threats.

Instructions

    List entities (hosts & accounts) in Vectra platform based on various filters. This tool returns entities with all their detailed information.

    Returns:
        str: Formatted string with list of detections.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_typeYesSelect type of entity to retrieve. Options are 'account' or 'host'.
stateNoFilter by entity state (active, inactive)active
orderingNoOrder by 'urgency_score', '-urgency_score', 'last_detection_timestamp', '-last_detection_timestamp', 'last_modified_timestamp', '-last_modified_timestamp', 'name', '-name'. The '-' prefix indicates descending order.urgency_score
nameNoFilter by entity name. Can also perform partial word match.
host_ipNoFilter by entity IP address. Only applicable for host entities.
is_prioritizedNoFilter for prioritized entities or non-prioritized entities. Defaults to True to return only prioritized entities.
tagsNoFilter for entities with a particular tag
limitNoMaximum number of detections to return in the batch. None means no limit

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it mentions the tool 'returns entities with all their detailed information,' it doesn't address critical behavioral aspects like whether this is a read-only operation, potential rate limits, authentication requirements, pagination behavior, or what happens when filters return no results. The description is insufficient for a tool with 8 parameters and no annotation coverage.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is reasonably concise with three sentences, but the structure is problematic. The second sentence 'Returns: str: Formatted string with list of detections.' contains a significant contradiction - it mentions 'detections' while the tool is about 'entities.' This error undermines the description's effectiveness despite its brevity.

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 tool's complexity (8 parameters, no annotations, but with output schema), the description is incomplete. While the output schema exists (reducing the need to explain return values), the description fails to address behavioral aspects, usage context, and contains a factual error about returning 'detections' instead of 'entities.' For a filtering tool with many parameters, more comprehensive guidance is needed.

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 the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema - it mentions 'various filters' and that it returns 'detailed information,' but provides no additional parameter semantics, syntax examples, or clarification beyond what's in the structured schema. This meets the baseline for high schema coverage.

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 tool's purpose: 'List entities (hosts & accounts) in Vectra platform based on various filters.' It specifies the resource (entities) and action (list) with filtering context. However, it doesn't explicitly differentiate from sibling tools like 'lookup_entity_info_by_name' or 'list_entity_detections', which prevents a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. With multiple sibling tools that also retrieve entity information (e.g., 'lookup_entity_info_by_name', 'get_account_details', 'get_host_details'), there's no indication of when this filtered listing approach is preferred over more specific lookup tools.

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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