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scriptedstatement

opencti-mcp

get_relationships

Retrieve relationships for a given entity, filtering by direction and relationship type to uncover connections like uses, indicates, and targets.

Instructions

Get relationships for an entity (who uses what, what indicates what, etc.).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default: 50, max: 50)
directionNoRelationship direction: 'from' (outgoing), 'to' (incoming), 'both' (default)both
entity_idYesEntity ID to get relationships for
relationship_typesNoFilter by relationship types (e.g., ['indicates', 'uses', 'targets'])

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.5.0

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral disclosure. It conveys that this is a read-style operation and gives semantic examples of relationship content, but it does not mention return format, pagination, or any side effects. This is adequate but not rich.

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 a single sentence with no wasted words. The core action and scope are front-loaded, and the parenthetical examples provide helpful context without bloat.

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?

For a four-parameter tool with full schema coverage and no output schema, the description gives enough to understand basic intent but does not describe what a relationship object looks like or what the return value contains. This is a meaningful gap, though not critical for invoking the tool.

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 fully documents all four parameters. The description adds slight semantic color with examples like 'uses' and 'indicates', which align with relationship_types, but it does not meaningfully compensate beyond the schema baseline.

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 states a specific verb (get) and resource (relationships) tied to an entity, with concrete examples ('who uses what, what indicates what') that clarify the tool's purpose. It clearly distinguishes itself from sibling search tools and get_entity.

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 clearly implies when to use this tool: when you need an entity's relationships, not when you need entity details or a search. It does not explicitly name alternatives or exclusions, but the context is sufficiently clear given the sibling tool set.

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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