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aws-athena-mcp

get_status

Check the current status of an AWS Athena query execution to monitor progress and determine when results are ready.

Instructions

Get the current status of a query execution

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryExecutionIdYesThe query execution ID

Implementation Reference

  • MCP tool handler for 'get_status': validates the queryExecutionId argument and delegates to AthenaService.getQueryStatus, returning the JSON-formatted status.
    case "get_status": {
      if (!request.params.arguments?.queryExecutionId ||
          typeof request.params.arguments.queryExecutionId !== 'string') {
        throw new McpError(
          ErrorCode.InvalidParams,
          "Missing or invalid required parameter: queryExecutionId (string)"
        );
      }
    
      const status = await this.athenaService.getQueryStatus(
        request.params.arguments.queryExecutionId
      );
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(status, null, 2),
          },
        ],
      };
    }
  • Input schema definition for the 'get_status' tool, specifying the required queryExecutionId parameter.
    {
      name: "get_status",
      description: "Get the current status of a query execution",
      inputSchema: {
        type: "object",
        properties: {
          queryExecutionId: {
            type: "string",
            description: "The query execution ID",
          },
        },
        required: ["queryExecutionId"],
      },
    },
  • Core implementation of query status retrieval using AWS AthenaClient.GetQueryExecutionCommand, extracting state, reasons, statistics, and handling errors.
    async getQueryStatus(queryExecutionId: string): Promise<QueryStatus> {
      try {
        const response = await this.client.send(
          new GetQueryExecutionCommand({
            QueryExecutionId: queryExecutionId,
          })
        );
    
        if (!response.QueryExecution) {
          throw {
            message: "Query execution not found",
            code: "QUERY_NOT_FOUND",
          };
        }
    
        return {
          state: response.QueryExecution.Status?.State || "UNKNOWN",
          stateChangeReason: response.QueryExecution.Status?.StateChangeReason,
          statistics: {
            dataScannedInBytes: response.QueryExecution.Statistics?.DataScannedInBytes || 0,
            engineExecutionTimeInMillis: response.QueryExecution.Statistics?.EngineExecutionTimeInMillis || 0,
          },
          substatementType: response.QueryExecution.SubstatementType,
        };
      } catch (error) {
        if (error instanceof InvalidRequestException) {
          throw {
            message: "Query execution not found",
            code: "QUERY_NOT_FOUND",
          };
        }
        throw error;
      }
    }
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 to 'Get' status, implying a read-only operation, but doesn't specify whether this requires authentication, has rate limits, or details the return format (e.g., pending, completed, error). The description is minimal and misses key behavioral traits for a tool interacting with query executions.

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, clear sentence with no wasted words, making it highly concise and front-loaded. It directly states the tool's purpose without unnecessary elaboration, which is efficient for an AI agent to parse and understand.

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 query execution tools and the lack of annotations and output schema, the description is incomplete. It doesn't explain what the status includes (e.g., progress indicators, error messages) or how it relates to sibling tools like 'get_result'. For a tool that likely returns dynamic execution state information, more context is needed to guide effective use.

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 input schema has 100% description coverage, with the single parameter 'queryExecutionId' documented as 'The query execution ID'. The description doesn't add any meaning beyond this, such as explaining where to obtain this ID or its format. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter documentation.

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 'Get' and the resource 'current status of a query execution', making the purpose specific and understandable. However, it doesn't explicitly distinguish this tool from its siblings like 'get_result' or 'run_query', which might also relate to query execution status or results.

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 'get_result' or 'run_query'. It lacks context about prerequisites, such as needing a query execution ID from a previous operation, and doesn't mention any exclusions or specific scenarios for its use.

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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