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tigergraph

tigergraph-mcp

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by tigergraph

tigergraph__get_nodes

Retrieve multiple vertices from a TigerGraph graph with optional filtering, sorting, and pagination.

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. Dates show when Glama detected each change.

  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?

With no annotations, the description carries the full burden of explaining behavior. It states that data is retrieved, returns complete vertex data, supports filters, sorting, and defaults (limit=100). It does not explicitly mention 'read-only' or absence of side effects, but the operation is clearly a retrieval. It could add a note about no mutation, but the current wording suffices for a read operation.

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). It is somewhat lengthy but each section serves a purpose and avoids redundancy. The front-loaded purpose and usage sections make it easy to scan.

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?

The description covers retrieval behavior, filtering, sorting, pagination, and default limit. It mentions return of complete vertex data but does not specify the output structure (since no output schema exists). It does not discuss edge cases or error conditions, but for a simple retrieval tool the coverage is adequate. Minor gap is the absence of explicit output format details.

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?

The schema already covers parameter descriptions at 100%. The tool description adds value through the 'Common Workflows' examples showing parameter usage (e.g., where='age > 25', sort='-created_at') and 'Tips' on combining parameters. This goes beyond the schema's static descriptions, though the schema alone is already comprehensive.

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 optional filtering and sorting. It explicitly differentiates from related tools like get_node (single vertex), get_vertex_count (counting), and run_query (complex multi-hop queries), making its purpose unambiguous.

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 (listing vertices, searching by criteria, browsing with pagination). It also provides 'Related Tools' with guidance on when to use alternatives, including a note that run_query is for complex multi-hop queries, giving clear when-to-use vs. when-not-to-use context.

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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