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octodet-elasticsearch-mcp

add_document

Insert or update documents into a specified Elasticsearch index, enabling structured data storage and retrieval for efficient search operations.

Instructions

Add a new document to a specific Elasticsearch index

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
documentYesDocument body to index
idNoOptional document ID (if not provided, Elasticsearch will generate one)
indexYesName of the Elasticsearch index

Implementation Reference

  • The handler function for the 'add_document' MCP tool. It calls the Elasticsearch service to add the document and returns a formatted response or error message.
    async ({ index, id, document }) => {
      try {
        const response = await esService.addDocument(index, document, id);
        return {
          content: [
            {
              type: "text",
              text: `Document added to index '${index}' with ID: ${response._id}`,
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: "text",
              text: `Error adding document: ${
                error instanceof Error ? error.message : String(error)
              }`,
            },
          ],
        };
      }
    }
  • Zod input schema defining parameters for the add_document tool: required index name, optional id, and document body.
    {
      index: z
        .string()
        .trim()
        .min(1, "Index name is required")
        .describe("Name of the Elasticsearch index"),
      id: z
        .string()
        .optional()
        .describe(
          "Optional document ID (if not provided, Elasticsearch will generate one)"
        ),
      document: z.record(z.any()).describe("Document body to index"),
    },
  • src/index.ts:416-457 (registration)
    Registration of the 'add_document' tool on the MCP server using server.tool, specifying name, description, input schema, and handler.
    server.tool(
      "add_document",
      "Add a new document to a specific Elasticsearch index",
      {
        index: z
          .string()
          .trim()
          .min(1, "Index name is required")
          .describe("Name of the Elasticsearch index"),
        id: z
          .string()
          .optional()
          .describe(
            "Optional document ID (if not provided, Elasticsearch will generate one)"
          ),
        document: z.record(z.any()).describe("Document body to index"),
      },
      async ({ index, id, document }) => {
        try {
          const response = await esService.addDocument(index, document, id);
          return {
            content: [
              {
                type: "text",
                text: `Document added to index '${index}' with ID: ${response._id}`,
              },
            ],
          };
        } catch (error) {
          return {
            content: [
              {
                type: "text",
                text: `Error adding document: ${
                  error instanceof Error ? error.message : String(error)
                }`,
              },
            ],
          };
        }
      }
    );
  • Supporting helper method in ElasticsearchService class that performs the core Elasticsearch client.index operation to add the document.
    async addDocument(index: string, document: any, id?: string): Promise<any> {
      const params: any = { index, document };
      if (id) params.id = id;
      return await this.client.index(params);
    }
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. While 'add a new document' implies a write operation, it doesn't specify permissions required, whether the index must exist, what happens on duplicate IDs, error conditions, or rate limits. This leaves significant behavioral gaps for a mutation 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, efficient sentence that states the core purpose without unnecessary words. It's appropriately sized for a straightforward indexing operation and front-loads the essential information.

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 write operation with no annotations and no output schema, the description is insufficient. It doesn't explain what happens on success/failure, return values, error handling, or how this differs from similar operations like 'update_document'. Given the complexity of Elasticsearch operations and lack of structured metadata, more context is needed.

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 all parameters are documented in the schema. The description adds no additional parameter semantics beyond what's already in the schema descriptions (e.g., 'Document body to index', 'Optional document ID', 'Name of the Elasticsearch index'). Baseline 3 is appropriate when schema does the heavy lifting.

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 ('add a new document') and target resource ('to a specific Elasticsearch index'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'update_document' or 'bulk', which would require more specific scope information.

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 'update_document', 'bulk', or 'create_index'. It doesn't mention prerequisites, constraints, or typical use cases, leaving the agent to infer usage from the tool name alone.

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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