Skip to main content
Glama
tigergraph

tigergraph-mcp

Official
by tigergraph

tigergraph__update_schema

Apply incremental schema changes by adding or dropping vertex types, edge types, or attributes on a specific graph or globally.

Instructions

Apply incremental schema changes: add/drop vertex types, edge types, or individual attributes. Supports both local (graph-scoped) and global schema changes.

Use When:

  • Adding new vertex or edge types to an existing graph (local)

  • Creating global vertex/edge types shared across graphs (global)

  • Dropping vertex or edge types that are no longer needed

  • Adding or removing attributes on existing vertex types

Local schema change (add a vertex type to a graph):

{
  "graph_name": "MyGraph",
  "add_vertex_types": [{"name": "Product", "attributes": [{"name": "price", "type": "FLOAT"}]}]
}

Global schema change (omit graph_name):

{
  "add_vertex_types": [{"name": "SharedVertex", "attributes": [{"name": "val", "type": "INT"}]}]
}

Tips:

  • Drop edges referencing a vertex type before dropping the vertex type

  • Adding attributes with defaults avoids null values on existing data

  • Use 'get_graph_schema' to inspect the current schema first

  • Omit 'graph_name' to apply changes at the global level

Related Tools: create_graph, get_graph_schema, show_graph_details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
profileNoConnection profile name. If not provided, uses TG_PROFILE env var or 'default'.
graph_nameNoName of the graph to modify. If not provided, runs a global schema change.
add_edge_typesNoEdge type definitions to add (same format as create_graph).
drop_edge_typesNoNames of edge types to drop.
add_vertex_typesNoVertex type definitions to add (same format as create_graph).
drop_vertex_typesNoNames of vertex types to drop.
add_vertex_attributesNoMap of vertex type name to list of attributes to add. E.g. {"Person": [{"name": "score", "type": "FLOAT"}]}
drop_vertex_attributesNoMap of vertex type name to list of attribute names to drop. E.g. {"Person": ["old_attr"]}

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, the description must carry the behavioral burden. It explains that types/attributes are added or dropped, and the tip about dropping edges before vertices implies cascading effects. However, it does not explicitly state irreversibility, failure conditions, or whether dropping a type also removes associated data. This leaves some behavioral ambiguity.

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 well-structured with clear sections: main description, 'Use When', examples, 'Tips', and 'Related Tools'. Every section adds value without redundancy. The text is concise yet comprehensive, achieving high information density per sentence.

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?

Given the tool's complexity (8 parameters, nested objects, local/global modes), the description provides sufficient context to call it correctly: when to use, how to format inputs, key safety tips, and related tools for schema inspection. No critical information is missing for an agent to understand the tool's role.

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?

The input schema provides descriptions for all 8 parameters, and the tool description gives examples for both local and global usage. The 'same format as create_graph' reference clarifies the structure for add_edge_types and add_vertex_types, and the JSON examples illustrate the nested object layout. Parameter meanings are fully covered.

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 purpose with specific verbs ('apply incremental schema changes') and resources ('vertex types, edge types, individual attributes'). It distinguishes local vs. global scope and explicitly relates to create_graph, making its role 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 'Use When' section lists concrete scenarios (adding/dropping types, global vs. local changes) and the 'Tips' section provides actionable guidance (drop edges before vertices, inspect schema first, omit graph_name for global). This gives agents clear conditions for invoking the tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/tigergraph/tigergraph-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server