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connectors_query

Pull live data from connected business sources like Shopify, Stripe, and Google Analytics using connector URIs for analysis and reporting.

Instructions

Pull live data from a connected source using connector:// URIs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYesConnector URI (e.g., connector://mcpanalytics_gsc/search_analytics?...)

Implementation Reference

  • The `CallToolRequestSchema` handler in `src/index.js` dynamically proxies all tool calls, including `connectors_query`, to the remote MCP server (`remoteClient.callTool`). The tools themselves are not implemented locally, but are fetched from the remote server's catalog at runtime.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      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,
        };
      }
    });
Behavior2/5

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

No annotations provided, so description carries full burden. Mentions 'live' (real-time behavior) but omits critical behavioral details: return format, pagination, caching behavior, rate limits, authentication requirements, and error handling. For a data retrieval tool with no output schema, this lack of behavioral context is a significant gap.

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?

Single sentence of 9 words with zero waste. Front-loaded with action verb 'Pull'. Appropriate length for a single-parameter tool, though the brevity contributes to gaps in other dimensions.

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?

Adequate for the schema complexity (1 simple string parameter with 100% coverage) but incomplete given zero annotations and no output schema. Lacks description of returned data structure, error conditions, or examples of valid connector URIs beyond the schema's inline example.

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 coverage is 100%, establishing baseline 3. Description reinforces the URI parameter by referencing 'connector:// URIs', aligning with the schema's example. However, it adds no semantic depth beyond the schema's description (e.g., no syntax rules, validation details, or composition guidance).

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?

Clear verb 'Pull' and resource 'live data from a connected source', with specific mechanism 'connector:// URIs'. Distinguishes from siblings like connectors_list (listing) and datasets_read (cached datasets) by emphasizing 'live' data and connector URIs. Slightly vague on what constitutes a 'connected source'.

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?

No explicit when-to-use guidance or comparison with alternatives. While 'live data' implies real-time use cases, there is no guidance on when to use this vs datasets_read, reports_view, or other data retrieval tools. No prerequisites or conditions 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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