tools_run

Instructions

Implementation Reference

• src/index.js:47-47 (schema)

  Schema definition for the 'tools_run' tool — it expects tool_name (string) and taskList (object with dataset, userContext, column_mapping, module_parameters).

  { name: "tools_run", description: "Execute an analysis tool. Returns a shareable interactive HTML report URL.", inputSchema: { type: "object", properties: { tool_name: { type: "string", description: "Name of the tool to execute" }, taskList: { type: "object", description: "Contains inputs: dataset, userContext, column_mapping, module_parameters" } }, required: ["tool_name", "taskList"] } },

• src/index.js:43-63 (registration)

  Static tool catalog that registers 'tools_run' along with all other tools as a fallback for inspection mode.

  const STATIC_TOOLS = [
    { name: "about", description: "Get platform info, pricing, usage stats, or documentation.", inputSchema: { type: "object", properties: { topic: { type: "string", description: "Topic: platform, pricing, current_usage, manual, or a docs section" } }, required: ["topic"] } },
    { name: "discover_tools", description: "Find analysis tools matching your data or question. Semantic search across 50+ statistical and ML tools.", inputSchema: { type: "object", properties: { query: { type: "string", description: "Text query describing what you want to analyze" }, dataset: { type: "string", description: "Dataset UUID to match tools against" } } } },
    { name: "tools_schema", description: "Get JSON schema for a tool — column_mapping and module_parameters required before tools_run.", inputSchema: { type: "object", properties: { tool_name: { type: "string", description: "Name of the tool" } }, required: ["tool_name"] } },
    { name: "tools_run", description: "Execute an analysis tool. Returns a shareable interactive HTML report URL.", inputSchema: { type: "object", properties: { tool_name: { type: "string", description: "Name of the tool to execute" }, taskList: { type: "object", description: "Contains inputs: dataset, userContext, column_mapping, module_parameters" } }, required: ["tool_name", "taskList"] } },
    { name: "tools_info", description: "Get detailed information about a specific analysis tool — use cases, assumptions, data requirements.", inputSchema: { type: "object", properties: { tool_name: { type: "string", description: "Name of the tool" } }, required: ["tool_name"] } },
    { name: "datasets_upload", description: "Generate a secure upload token for CSV files. Returns UUID + curl command for the user.", inputSchema: { type: "object", properties: { expires_in: { type: "integer", description: "Token expiration in seconds", default: 300 } } } },
    { name: "datasets_list", description: "List and search uploaded datasets with fuzzy matching.", inputSchema: { type: "object", properties: { search: { type: "string", description: "Search by name, description, or tags" }, limit: { type: "integer", description: "Max results", default: 20 } } } },
    { name: "datasets_read", description: "Read dataset contents — preview rows, columns, and types.", inputSchema: { type: "object", properties: { uuid: { type: "string", description: "Dataset UUID" }, secret: { type: "string", description: "Dataset secret key" }, rows: { type: "integer", description: "Number of rows to preview", default: 10 } }, required: ["uuid"] } },
    { name: "datasets_download", description: "Generate a single-use download token for securely downloading datasets.", inputSchema: { type: "object", properties: { uuid: { type: "string", description: "Dataset UUID" } }, required: ["uuid"] } },
    { name: "datasets_update", description: "Update dataset metadata — name, description, tags, visibility.", inputSchema: { type: "object", properties: { uuid: { type: "string", description: "Dataset UUID" } }, required: ["uuid"] } },
    { name: "connectors_list", description: "List available data connectors — GA4, Google Search Console, and more.", inputSchema: { type: "object", properties: {} } },
    { name: "connectors_query", description: "Pull live data from a connected source using connector:// URIs.", inputSchema: { type: "object", properties: { uri: { type: "string", description: "Connector URI (e.g., connector://mcpanalytics_gsc/search_analytics?...)" } }, required: ["uri"] } },
    { name: "reports_list", description: "List analysis reports with metadata.", inputSchema: { type: "object", properties: { limit: { type: "integer", description: "Max results", default: 10 } } } },
    { name: "reports_search", description: "Search reports by job ID, tool name, or keyword.", inputSchema: { type: "object", properties: { query: { type: "string", description: "Search query" }, job_ids: { type: "array", items: { type: "string" }, description: "Filter by processing IDs" } } } },
    { name: "reports_view", description: "View a specific report by processing ID.", inputSchema: { type: "object", properties: { processing_id: { type: "string", description: "Processing ID from tools_run" } }, required: ["processing_id"] } },
    { name: "report_cards", description: "Get individual card data from a report for rendering.", inputSchema: { type: "object", properties: { processing_id: { type: "string" } }, required: ["processing_id"] } },
    { name: "agent_advisor", description: "Conversational AI that guides analysis and interprets results.", inputSchema: { type: "object", properties: { message: { type: "string", description: "Your question or request" } }, required: ["message"] } },
    { name: "billing", description: "Check credit balance, subscription status, or open billing portal.", inputSchema: { type: "object", properties: { action: { type: "string", enum: ["status", "portal", "usage"], description: "Billing action", default: "status" } } } },
    { name: "module_request", description: "Request a custom analysis module to be built for your use case.", inputSchema: { type: "object", properties: { description: { type: "string", description: "Describe the analysis you need" } }, required: ["description"] } },
  ];

• src/index.js:121-146 (handler)

  Generic CallTool handler that proxies all tool calls (including 'tools_run') to the remote MCP server via remoteClient.callTool(). This is the execution path for 'tools_run'.

  server.setRequestHandler(CallToolRequestSchema, async (request) => {
    if (!remoteClient) {
      return {
        content: [
          {
            type: "text",
            text: "MCP Analytics API key required. Set MCP_ANALYTICS_API_KEY in your environment.\nGet a free key at https://app.mcpanalytics.ai",
          },
        ],
        isError: true,
      };
    }
  
    try {
      const result = await remoteClient.callTool({
        name: request.params.name,
        arguments: request.params.arguments || {},
      });
      return result;
    } catch (err) {
      return {
        content: [{ type: "text", text: `Error: ${err.message}` }],
        isError: true,
      };
    }
  });