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Amazon Neptune MCP Server

Amazon Neptune MCP Server

by AkM-2018
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_graph_schema

Retrieve the graph schema to identify vertex and edge labels along with their connection patterns for query planning and data exploration.

Instructions

Get the schema for the graph including the vertex and edge labels as well as the (vertex)-[edge]->(vertex) combinations.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_graph_schema"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

B3.2/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool returns (schema information) but lacks details on permissions, rate limits, error handling, or response format. For a tool with zero annotation coverage, this is insufficient, scoring a 2 due to missing critical behavioral context.

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 concise and well-structured, using two sentences that efficiently convey the tool's purpose. It front-loads the main action ('Get the schema') and adds specific details without waste, making it easy to parse. Every sentence earns its place, justifying a score of 5.

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

Completeness3/5

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

Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate but has clear gaps. It explains what the tool retrieves but lacks output details or behavioral context, which is needed for full completeness. This meets the minimum viable standard, scoring a 3.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose without redundant parameter details. This aligns with the baseline of 4 for zero-parameter tools, as it adds value by explaining what the tool does without unnecessary repetition.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 ('Get the schema for the graph') and resources ('vertex and edge labels', 'combinations'), making it easy to understand what it does. It doesn't explicitly distinguish from sibling tools like 'get_graph_status' or query tools, but the focus on schema retrieval is distinct enough for a 4.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_graph_status' for status checks or query tools for data retrieval, leaving the agent without context for tool selection. This lack of comparative usage information results in a score of 2.

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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