Tool: GOOGLE_SEARCH_CONSOLE-RETRIEVE-SITE-PERFORMANCE-DATA Problem: Major data discrepancy between MCP tool results and actual Google Search Console interface

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1

Issue Summary:

Tool: GOOGLE_SEARCH_CONSOLE-RETRIEVE-SITE-PERFORMANCE-DATA

Problem: Major data discrepancy between MCP tool results and actual Google Search Console interface

Specific Details to Include:

1. The Discrepancy:

  • MCP Tool Result: 315 clicks, 72,392 impressions for “xxxl shirt size” (90 days)
  • Actual GSC Interface: 8 clicks, 1,694 impressions for “xxxl shirt size” (3 months)
  • Difference: ~4,000% variance in impressions

2. My Exact Function Call:

GOOGLE_SEARCH_CONSOLE-RETRIEVE-SITE-PERFORMANCE-DATA
Parameter: "Get the exact raw performance data for thetiebar.com for the query 'xxxl shirt size' specifically for the last 90 days. Include the precise clicks, impressions, CTR, and average position for this exact query."

3. Questions for Pipedream:

  • Are there known issues with GSC data accuracy in the MCP tool?
  • Does the tool use different date ranges, filters, or API endpoints than the standard GSC interface?
  • How can we verify what actual API parameters are being sent to Google?
  • Is there a way to see the raw API request/response for debugging?

4. What I Need:

  • Reliable way to get GSC data that matches the interface
  • Ability to verify API parameters being used
  • Transparency into what might cause such large discrepancies

5. Impact:

  • This prevents reliable SEO analysis since we can’t trust the data
  • Need to know if this affects other GSC data pulls or just specific queries

Possible Causes to Investigate:

  1. Date Range Issues: Tool might be using different date ranges despite “90 days” instruction
  2. Property Selection: Could be pulling from wrong GSC property
  3. Query Matching: Might be aggregating multiple related queries
  4. API Endpoint Differences: Different GSC API endpoints return different data
  5. Filter Problems: Unexpected filters being applied

This level of data inaccuracy makes the tool unreliable for professional SEO work, so getting this resolved is critical.

2

Hi @vlado,

To address the discrepancies you’re experiencing with the Google Search Console (GSC) data retrieved through the MCP tool, let’s consider the following points:

1. Known Issues with GSC Data Accuracy

There are no specific known issues with GSC data accuracy in the MCP tool documented in the Pipedream documentation. However, discrepancies can arise due to various factors such as differences in date ranges, filters, or API endpoints used.

2. Date Ranges, Filters, and API Endpoints

  • Date Ranges: Ensure that the date range specified in the API request matches the one you are comparing in the GSC interface. Sometimes, tools might default to different date ranges.
  • Filters: Check if any additional filters are being applied in the MCP tool that might not be present in the GSC interface.
  • API Endpoints: Different endpoints might return different data. Ensure that the endpoint used in the MCP tool matches the one you expect.

3. Verifying API Parameters

To verify the API parameters being sent to Google, you can log the request details in your Pipedream workflow. Here’s how you can capture and log the request:

import { axios } from "@pipedream/platform";

export default defineComponent({
  props: {
    google_search_console: {
      type: "app",
      app: "google_search_console",
    },
  },
  async run({ steps, $ }) {
    const response = await axios($, {
      url: `https://www.googleapis.com/webmasters/v3/sites/your-site-url/searchAnalytics/query`,
      method: "POST",
      headers: {
        Authorization: `Bearer ${this.google_search_console.$auth.oauth_access_token}`,
      },
      data: {
        startDate: "2023-01-01",
        endDate: "2023-03-31",
        dimensions: ["query"],
        searchType: "web",
        dimensionFilterGroups: [{
          filters: [{
            dimension: "query",
            operator: "equals",
            expression: "xxxl shirt size"
          }]
        }]
      }
    });
    
    console.log("Request Data:", {
      startDate: "2023-01-01",
      endDate: "2023-03-31",
      dimensions: ["query"],
      searchType: "web",
      dimensionFilterGroups: [{
        filters: [{
          dimension: "query",
          operator: "equals",
          expression: "xxxl shirt size"
        }]
      }]
    });

    return response;
  },
});

4. Debugging API Requests

To see the raw API request/response, you can log the request and response details as shown in the code snippet above. This will help you verify the exact parameters being used and identify any discrepancies.

5. Ensuring Reliable Data

  • Consistency: Make sure the parameters used in the API call are consistent with those in the GSC interface.
  • Property Selection: Verify that the correct GSC property is being queried.
  • Query Matching: Ensure that the query is not aggregating multiple related queries.

6. Impact and Resolution

Understanding the root cause of the discrepancy is crucial for reliable SEO analysis. By verifying the API parameters and ensuring consistency with the GSC interface, you can improve the reliability of the data.

If you continue to experience issues, consider reaching out to Pipedream support for further assistance: Pipedream.

By following these steps, you should be able to identify and resolve the discrepancies in the GSC data retrieved through the MCP tool.

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