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datasets_upload

Generate a secure upload token for CSV files to enable data analysis. Returns a UUID and curl command.

Instructions

Generate a secure upload token for CSV files. Returns UUID + curl command for the user.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expires_inNoToken expiration in seconds

Implementation Reference

  • Schema/registration entry for 'datasets_upload' tool in the static catalog. Defines the tool name, description ('Generate a secure upload token for CSV files'), and input schema (optional 'expires_in' integer, default 300).
    { 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 } } } },
  • src/index.js:43-63 (registration)
    The STATIC_TOOLS array where 'datasets_upload' is registered as one of many tools. This static catalog is used as fallback when the remote server is unreachable.
    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"] } },
    ];
  • Generic CallToolRequestSchema handler that proxies all tool calls (including datasets_upload) to the remote MCP server via remoteClient.callTool(). No specific handler for datasets_upload exists locally; execution is entirely delegated to the remote API.
    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,
        };
      }
    });
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It states that the tool returns a UUID and curl command, implying a token generation action. However, it does not disclose side effects, authentication requirements, or any limitations. The security implications are hinted but not elaborated.

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 sentence with no extraneous words. It efficiently conveys the purpose and output.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple token generation tool with one parameter, the description covers the basics. However, it does not explain how the token is used, whether it is associated with a specific dataset, or the overall upload workflow. The absence of output schema leaves the agent to guess the response structure.

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 the parameter 'expires_in' is fully documented in the schema. The description adds context about CSV file upload and return format but does not enhance understanding of the parameter beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool generates a secure upload token for CSV files, specifying output as UUID and curl command. It uses a specific verb and resource, distinguishing it from sibling tools like datasets_download or datasets_read.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly state when to use this tool vs alternatives. While it's obvious for uploading CSVs, there is no guidance on when not to use it or if there are prerequisites. Sibling tools are not mentioned.

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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