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tigergraph

tigergraph-mcp

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by tigergraph

tigergraph__show_graph_details

Show details of a specific TigerGraph graph, including schema, queries, loading jobs, and data sources. Optionally filter by detail type (schema, query, loading_job, data_source) for targeted information.

Instructions

Show details of a specific graph. By default shows everything (schema, queries, loading jobs, data sources). Use 'detail_type' to show only a specific category.

Use When: • You need a full picture of a graph (schema + queries + jobs) • Starting work with a graph (call this first!) • Checking which queries or loading jobs are installed • Debugging schema or job issues

Quick Start:

{ "graph_name": "SocialNetwork" }

(Shows everything under the graph)

Filter by category:

{ "graph_name": "SocialNetwork", "detail_type": "query" }

Options: 'schema', 'query', 'loading_job', 'data_source'

Tips: • No detail_type → shows all (GSQL LS output) • For structured JSON schema, use 'get_graph_schema' instead • For just graph names, use 'list_graphs' • For vector attributes, use 'list_vector_attributes' instead

Related Tools: get_graph_schema (schema JSON), list_graphs (names only), list_vector_attributes (vector attribute details)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileNoConnection profile name. Omit to use the active default profile. Use 'list_connections' to see available profiles.
graph_nameNoName of the graph. If not provided, uses default connection.
detail_typeNoWhich details to show. Options: 'schema' (vertex/edge types), 'query' (installed queries), 'loading_job' (loading jobs), 'data_source' (data sources). If not provided, shows everything (equivalent to GSQL LS).

Schema Changelog

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

  1. First observedv1.0.2

TDQS

A4.8/5.0
Behavior4/5

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

With no annotations given, the description carries the transparency burden. It accurately describes read-only behavior and default or filtered output categories, but it does not explicitly state 'no modifications' or describe failure modes such as missing graphs; still, this is a low-risk inspection tool.

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 structured into summary, usage scenarios, quick-start examples, and related tools, with no filler. Although slightly long, every sentence adds actionable information for selecting and invoking the tool.

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?

The description covers the tool's scope (schema, queries, loading jobs, data sources), default behavior, filtering options, and related tools for structured output. It does not provide an output schema, but the absence is mitigated by clear category descriptions and the pointer to get_graph_schema for JSON.

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

Parameters5/5

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

All three parameters are described individually in the schema, and the description adds examples and default behavior: detail_type's allowed values are enumerated, graph_name defaults to the connection, and profile fallback is explained. This makes parameter usage unambiguous.

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's function: showing graph details across schema, queries, loading jobs, and data sources. It also names overlapping tools (get_graph_schema, list_graphs) to help distinguish when this one should be used.

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 'Use When' section explicitly lists scenarios: needing a full picture, starting work, checking queries or jobs, and debugging. It also provides direct alternatives for structured schema or vector attributes, so an agent can choose correctly.

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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