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Bulk Create Graph Nodes

bulk_create_graph_nodes

Create multiple nodes at once (up to 500 per call). Uses Neo4j UNWIND for high performance.

Essential for knowledge graph population — create hundreds of entities from a single book chapter or article.

Each node needs: entity_id (unique string) and data (properties dict).

Example: entity_type: "concept" nodes: [ {"entity_id": "quantum-mechanics-001", "data": {"name": "Quantum Mechanics", "field": "Physics"}}, {"entity_id": "wave-function-001", "data": {"name": "Wave Function", "field": "Physics"}}, {"entity_id": "superposition-001", "data": {"name": "Superposition", "field": "Physics"}} ]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nodesYesList of nodes. Each: {entity_id: string, data: {properties}}
project_idYesProject ID (UUID)
entity_typeYesEntity key for all nodes
environmentNoEnvironment: staging or production (default: staging)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false, and idempotentHint=false. The description adds genuine context beyond them: the 500-node ceiling, UNWIND-based performance, and the required per-node shape. However it omits duplicate entity_id handling and what a failure mid-batch does, which matters for a non-idempotent write.

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?

Front-loaded with the core action and limit in the first sentence, then the use case, then the per-node contract. The worked example is longer than strictly necessary but earns its place by showing the data dict shape.

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?

For a batch mutation tool with rich annotations and full schema coverage but no output schema, the essentials are present. Still missing return-value/error behavior and the consequence of re-submitting an existing entity_id, which an agent needs before bulk-loading.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all four parameters and the nested node shape; the baseline is 3. The description's example and the '(unique string)' note on entity_id add modest value (uniqueness is not in the schema) but do not substantially extend the parameter semantics.

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?

States a specific verb (create), resource (graph nodes), and scope (multiple at once, up to 500 per call). An agent can distinguish it from the single-node sibling create_graph_node and from bulk_create_graph_relationships purely from the description.

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

Usage Guidelines4/5

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

Gives clear context for when to reach for it ('knowledge graph population — create hundreds of entities from a single book chapter or article') and implies the single-node alternative via 'multiple nodes at once'. No explicit when-not-use or named sibling, so it falls short of a 5.

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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