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StevenWangler

MCP Memory Server

create_entities

Add multiple entities, including names, types, and associated observations, into a knowledge graph for persistent memory and reasoning across conversations in the MCP Memory Server.

Instructions

Create multiple new entities in the knowledge graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entitiesYes

Implementation Reference

  • The core handler function in KnowledgeGraphManager that executes the tool logic: loads the graph, filters out duplicate entities by name, appends new ones, saves the graph, and returns the newly created entities.
    async createEntities(entities: Entity[]): Promise<Entity[]> {
      const graph = await this.loadGraph();
      const newEntities = entities.filter(e => !graph.entities.some(existingEntity => existingEntity.name === e.name));
      graph.entities.push(...newEntities);
      await this.saveGraph(graph);
      return newEntities;
  • TypeScript interface defining the structure of an Entity, used as the type for inputs to createEntities.
    interface Entity {
      name: string;
      entityType: string;
      observations: string[];
    }
  • src/index.ts:202-227 (registration)
    Tool registration in the listTools response, including name, description, and detailed inputSchema matching the Entity structure.
    {
      name: "create_entities",
      description: "Create multiple new entities in the knowledge graph",
      inputSchema: {
        type: "object",
        properties: {
          entities: {
            type: "array",
            items: {
              type: "object",
              properties: {
                name: { type: "string", description: "The name of the entity" },
                entityType: { type: "string", description: "The type of the entity" },
                observations: { 
                  type: "array", 
                  items: { type: "string" },
                  description: "An array of observation contents associated with the entity"
                },
              },
              required: ["name", "entityType", "observations"],
            },
          },
        },
        required: ["entities"],
      },
    },
  • Dispatch case in the CallToolRequestSchema handler that invokes the createEntities method and formats the response.
    case "create_entities":
      return { content: [{ type: "text", text: JSON.stringify(await knowledgeGraphManager.createEntities(args.entities as Entity[]), null, 2) }] };

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
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 only states that it creates entities, but does not mention potential duplicate handling, overwrite behavior, validation rules, or whether the operation is atomic—information an agent would need for a mutating 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 a single, front-loaded sentence that communicates the core purpose with no filler. It is appropriately concise for a simple tool.

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

Completeness2/5

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

Given the absence of annotations, an output schema, and limited schema coverage, the description should offer more context about usage, side effects, or return behavior. It does not, leaving significant gaps for an agent to make assumptions about how the tool behaves.

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

Parameters2/5

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

The schema's top-level 'entities' parameter has no description (coverage 0%), and the tool description does not explain what constitutes an entity (name, type, observations). The description adds no value beyond the bare phrase 'multiple new entities,' failing to compensate for the schema gap.

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 uses a specific verb ('Create') and a specific resource ('multiple new entities in the knowledge graph'), clearly distinguishing this from sibling tools like create_relations and add_observations. It is explicit and unambiguous.

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 does not mention create_relations, add_observations, or any exclusions, leaving the agent to infer selection based solely on the name.

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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