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tigergraph-mcp

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Python
Hybrid

tigergraph__get_nodes

Read-onlyIdempotent

Retrieve graph vertices of a specific type with optional filtering, sorting, and pagination to browse data or find matching records.

Instructions

Purpose: Retrieve multiple vertices (nodes) from the graph with optional filtering and sorting.

When to Use:

  • List vertices of a specific type

  • Search for vertices matching certain criteria

  • Browse graph data with pagination

  • Find vertices based on attribute values

Key Features:

  • WHERE clause for filtering

  • Sorting by attributes (ascending/descending)

  • Limit results for pagination

  • Returns complete vertex data including all attributes

Common Workflows:

  1. List all vertices: get_nodes(vertex_type='Person', limit=10)

  2. Filter by attribute: get_nodes(vertex_type='Person', where='age > 25')

  3. Sort results: get_nodes(vertex_type='Person', sort='-created_at', limit=20)

Tips:

  • Use limit to avoid retrieving too many vertices

  • WHERE clause syntax follows TigerGraph conventions

  • Sort with '-' prefix for descending order

  • Combine where, sort, and limit for precise queries

Related Tools:

  • get_node: Get a single specific vertex

  • get_vertex_count: Count vertices before retrieving

  • run_query: For complex multi-hop queries

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sortNoSort results by attribute. Use '-' prefix for descending (e.g., '-age')
limitNoMaximum number of vertices to return (default: 100)
whereNoOptional filter condition. Use TigerGraph WHERE syntax. Examples: - 'age > 25' - 'name == "John"' - 'active == true'
profileNoConnection profile name. Omit to use the active default profile. Use 'list_connections' to see available profiles.
graph_nameNoName of the graph to query (uses default if not specified)
vertex_typeYesThe type of vertices to retrieve

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral context: it returns complete vertex data including all attributes, supports WHERE/sort/limit, and warns to use limit to avoid retrieving too many vertices. It doesn't mention pagination details or potential performance implications beyond the limit tip, but the annotations carry the main safety burden.

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, Key Features, Common Workflows, Tips, Related Tools) and front-loads the purpose. It is somewhat longer than strictly necessary, but every section earns its place by providing actionable guidance. The examples are compact and illustrative.

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?

For a read-only list tool with 100% schema coverage and no output schema, the description covers the key aspects an agent needs: what it does, when to use it, how to filter/sort/limit, and how it relates to siblings. It doesn't describe the exact return format, but since there is no output schema and the tool returns 'complete vertex data', this is a minor gap. The description is complete enough for correct invocation.

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 schema already documents all six parameters. The description adds value by showing concrete usage examples (e.g., where='age > 25', sort='-created_at') and explaining the '-' prefix for descending order, which reinforces the schema's parameter descriptions. It doesn't add much beyond the schema, but the examples and tips make the parameter semantics more accessible.

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 tool retrieves multiple vertices with filtering and sorting, using a specific verb ('Retrieve') and resource ('vertices/nodes'). It distinguishes itself from related tools by explicitly naming get_node (single vertex) and get_vertex_count (count before retrieving), so an agent can tell them apart.

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 (list vertices of a type, search by criteria, browse with pagination, find by attribute values), and the 'Related Tools' section explicitly names alternatives and when they are preferable (get_node for a single vertex, get_vertex_count before retrieving, run_query for complex multi-hop queries). This is explicit when/when-not guidance.

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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