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modelcontextprotocol

Knowledge Graph Memory Server

create_relations

Define and establish connections between entities in a knowledge graph by specifying source, target, and relation type to enhance structured memory storage and retrieval.

Instructions

Create multiple new relations between entities in the knowledge graph. Relations should be in active voice

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
relationsYes

Implementation Reference

  • The MCP tool handler for 'create_relations', which invokes KnowledgeGraphManager.createRelations and formats the response.
      const result = await knowledgeGraphManager.createRelations(relations);
      return {
        content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }],
        structuredContent: { relations: result }
      };
    }
  • Core logic in KnowledgeGraphManager to create (add if not duplicate) relations to the persistent graph.
    async createRelations(relations: Relation[]): Promise<Relation[]> {
      const graph = await this.loadGraph();
      const newRelations = relations.filter(r => !graph.relations.some(existingRelation => 
        existingRelation.from === r.from && 
        existingRelation.to === r.to && 
        existingRelation.relationType === r.relationType
      ));
      graph.relations.push(...newRelations);
      await this.saveGraph(graph);
      return newRelations;
    }
  • Registration of the 'create_relations' MCP tool with its schema and handler.
    // Register create_relations tool
    server.registerTool(
      "create_relations",
      {
        title: "Create Relations",
        description: "Create multiple new relations between entities in the knowledge graph. Relations should be in active voice",
        inputSchema: {
          relations: z.array(RelationSchema)
        },
        outputSchema: {
          relations: z.array(RelationSchema)
        }
      },
      async ({ relations }) => {
        const result = await knowledgeGraphManager.createRelations(relations);
        return {
          content: [{ type: "text" as const, text: JSON.stringify(result, null, 2) }],
          structuredContent: { relations: result }
        };
      }
    );
  • Zod schema for individual Relation objects, used in the input/output schemas for create_relations.
    const RelationSchema = z.object({
      from: z.string().describe("The name of the entity where the relation starts"),
      to: z.string().describe("The name of the entity where the relation ends"),
      relationType: z.string().describe("The type of the relation")
    });
  • TypeScript interface defining the structure of a Relation.
    export interface Relation {
      from: string;
      to: string;
      relationType: string;
    }
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states this creates relations (implying mutation) but doesn't disclose permissions needed, whether relations are reversible, error handling, or rate limits. The 'active voice' note is trivial and doesn't address core behavioral traits.

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?

The description is brief and to the point with two sentences, avoiding unnecessary verbosity. However, the second sentence about 'active voice' feels misplaced and doesn't contribute meaningfully to tool understanding, slightly reducing efficiency.

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?

For a mutation tool with no annotations, 0% schema coverage, and no output schema, the description is inadequate. It lacks details on prerequisites, side effects, response format, and error conditions, leaving significant gaps in understanding how to invoke and interpret results.

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?

Schema description coverage is 0%, so the description must compensate but fails to do so. It mentions 'relations' but doesn't explain the structure, required fields, or constraints beyond what's in the schema. The 'active voice' requirement adds no parameter clarity, leaving semantics largely undocumented.

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 action ('Create multiple new relations') and resource ('between entities in the knowledge graph'), which is specific and actionable. However, it doesn't explicitly differentiate from sibling tools like 'create_entities' or 'delete_relations', which would require more precise boundary definition.

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 like 'create_entities' or 'delete_relations'. The mention of 'active voice' is a stylistic requirement rather than usage context, leaving the agent with no practical decision-making criteria.

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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