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YuNaga224

Obsidian Memory MCP

by YuNaga224

create_entities

Add multiple entities to your knowledge graph by defining names, types, and observations for structured memory storage in Obsidian.

Instructions

Create multiple new entities in the knowledge graph

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entitiesYes

Implementation Reference

  • The main handler function for the create_entities tool. It loads the current knowledge graph, checks if each provided entity already exists, saves new entities to individual markdown files using saveEntity, and returns the list of newly created entities.
    async createEntities(entities: Entity[]): Promise<Entity[]> {
      const graph = await this.loadGraph();
      const newEntities: Entity[] = [];
      
      for (const entity of entities) {
        // Check if entity already exists
        if (graph.entities.some(e => e.name === entity.name)) {
          continue;
        }
        
        // Save the entity
        await this.saveEntity(entity, []);
        newEntities.push(entity);
      }
      
      return newEntities;
    }
  • Input schema (JSON Schema) for validating the arguments to the create_entities tool: requires an array of entities each with name, entityType, and observations.
    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"],
    },
  • index.ts:29-54 (registration)
    Registration of the create_entities tool in the MCP server's listTools response, including name, description, and reference to input schema.
    {
      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"],
      },
    },
  • index.ts:211-212 (registration)
    Tool call dispatcher in the CallToolRequestHandler: handles incoming calls to create_entities by invoking the storageManager handler and returning JSON-formatted result.
    case "create_entities":
      return { content: [{ type: "text", text: JSON.stringify(await storageManager.createEntities(args.entities as Entity[]), null, 2) }] };
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 states the action is a creation operation, implying mutation, but lacks details on permissions, idempotency, error handling, or rate limits. For a batch creation tool with zero annotation coverage, this is insufficient to inform the agent about critical behavioral traits beyond the basic 'create' intent.

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, efficient sentence that front-loads the core action ('Create multiple new entities') and specifies the context ('in the knowledge graph'). There is no wasted verbiage, making it highly concise and well-structured for quick comprehension.

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 complexity of a batch creation tool with no annotations, no output schema, and low schema description coverage (0%), the description is incomplete. It fails to address behavioral aspects like side effects, return values, or error conditions, and doesn't clarify usage relative to siblings, leaving significant gaps for the agent to operate effectively.

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?

The description mentions 'multiple new entities', which aligns with the 'entities' array parameter in the schema, but adds no semantic details beyond what the schema implicitly suggests. With 0% schema description coverage, the schema lacks descriptions for the 'entities' parameter itself, but the description doesn't compensate by explaining what entities consist of or how they're structured, leaving the agent reliant on the nested schema properties alone.

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 verb 'create' and the resource 'entities in the knowledge graph', with the additional detail 'multiple new' indicating batch creation. However, it doesn't explicitly differentiate from sibling tools like 'create_relations' or 'add_observations', which would require more specific language about what entities are versus relations or observations.

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 prerequisites (e.g., whether entities must be unique), exclusions (e.g., when to use 'add_observations' instead for existing entities), or comparisons to siblings like 'create_relations' for different resource types, leaving the agent to infer usage context.

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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