Skip to main content
Glama
tigergraph

tigergraph-mcp

Official
by tigergraph
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

tigergraph__get_node_edges

Read-onlyIdempotent

Retrieve all outgoing edges from a specific vertex to analyze its connections, including edge types, attributes, and target vertices. Filter by edge type for focused relationship exploration.

Instructions

Purpose: Retrieve all edges connected to a specific vertex (node).

When to Use:

  • Explore connections from a vertex

  • Find relationships of a specific type

  • Analyze node connectivity patterns

  • Get edge attributes and target vertices

What You Get:

  • Edge type and ID

  • Edge attributes

  • Target vertex information

  • Edge direction (outgoing from the specified vertex)

Common Workflows:

  1. Explore all connections: get_node_edges(vertex_type='Person', vertex_id='123')

  2. Specific relationship type: get_node_edges(..., edge_type='FRIEND_OF')

  3. Degree analysis: Count returned edges to get outgoing degree

Tips:

  • Returns OUTGOING edges only (edges starting from this vertex)

  • Use get_node_degree() for quick connection count

  • Use get_neighbors() to get target vertices without edge details

  • Combine with pagination (limit) for highly connected vertices

Note: This returns edges where the specified vertex is the SOURCE. For incoming edges, use a reverse traversal query or get_neighbors().

Related Tools:

  • get_node_degree: Count connections without retrieving edges

  • get_neighbors: Get connected vertices

  • get_edges: Query edges by type across the graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of edges to return (default: 100)
profileNoConnection profile name. Omit to use the active default profile. Use 'list_connections' to see available profiles.
edge_typeNoOptional: Filter by specific edge type. If omitted, returns all edge types.
vertex_idYesThe unique identifier of the source vertex
graph_nameNoName of the graph (uses default if not specified)
vertex_typeYesThe type of the source vertex

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior, so the description correctly adds non-obvious behavioral context beyond that: 'Returns OUTGOING edges only (edges starting from this vertex)' and 'This returns edges where the specified vertex is the SOURCE.' It also discloses the return contents, including edge attributes, target vertices, and direction.

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 well-structured with clear sections: Purpose, When to Use, What You Get, Common Workflows, Tips, Note, and Related Tools. It is slightly repetitive about the outgoing-edge constraint, mentioning it in What You Get, Tips, and Note, but it remains readable and front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having no output schema, the description compensates by listing what the agent receives: edge type, edge ID, edge attributes, target vertex information, and direction. It also covers common workflows, pagination advice, and clear comparisons to sibling tools, making the tool safe and effective to invoke.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3, but the description adds value with concrete usage examples like get_node_edges(vertex_type='Person', vertex_id='123') and explains how edge_type, limit, and vertex identity are used in practice. It does not duplicate every parameter's schema text but adds meaningful usage context.

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 opens with a specific verb and resource: 'Retrieve all edges connected to a specific vertex (node).' It clearly distinguishes itself from related siblings by stating that it returns outgoing edges only, and it explicitly differentiates from get_edges, get_neighbors, and get_node_degree in the Related Tools section.

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

Usage Guidelines5/5

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

The 'When to Use' section lists concrete scenarios, and the 'Tips' section gives explicit alternatives: 'Use get_node_degree() for quick connection count' and 'Use get_neighbors() to get target vertices without edge details.' It also states when not to use this tool, such as for incoming edges, which is strong routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools