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GrafeoDB

grafeo-mcp

Official
by GrafeoDB

create_node

Add a new node to a graph database with specified labels and optional properties. Ideal for inserting a single entity like a person or company.

Instructions

Create a new node in the graph with the given labels and properties.

Use this tool when: you need to add a single new entity to the graph. Do NOT use this for: bulk inserts (use execute_gql with INSERT/CREATE statements) or creating relationships (use create_edge).

Args: labels: One or more node labels (e.g. ["Person"] or ["Person", "Employee"]). properties: Optional key-value properties (e.g. {"name": "Alice", "age": 30}). Omit or pass null for a node with no properties.

Returns: JSON with the created node's id, labels, and properties.

Examples: create_node(["Person"], {"name": "Alice", "age": 30}) create_node(["Company"], {"name": "Acme", "founded": 2010}) create_node(["Tag"]) # no properties

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelsYes
propertiesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description must cover behavioral traits. It describes return format but lacks details on idempotency, validation, or side effects (e.g., what happens if node already exists). The examples and return info are helpful but not exhaustive.

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?

Well-structured with clear sections (when to use, args, returns, examples). However, it could be slightly more concise; the two-line examples are useful but verbose. No wasted sentences overall.

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?

Given the tool has output schema (not shown but present), the description adequately covers purpose, parameters, and usage. It does not mention error handling or edge cases, but given low complexity (2 params, 1 required), it is largely complete.

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 has 0% description coverage, so the description carries full burden. It explains labels as string array and properties as optional key-value object, with examples showing usage and optionality (null for no properties). This adds significant meaning beyond the raw schema.

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 verb and resource: 'Create a new node in the graph'. It distinguishes this tool from siblings like create_edge and execute_gql by specifying it's for single entities only.

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?

Explicitly provides when to use ('add a single new entity') and when not to ('bulk inserts' or 'creating relationships'), with alternative tools named (execute_gql, create_edge).

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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