Ekamoira Google Search Console MCP

Product Introduction

1. Definition: The Ekamoira Google Search Console MCP (Model-Controller-Presenter) is a specialized middleware server that bridges Google Search Console (GSC) data with large language models (LLMs) like ChatGPT, Claude, and Cursor. It operates as a secure API layer, enabling real-time querying of GSC data via natural language commands.
2. Core Value Proposition: It eliminates manual CSV exports and AI hallucination errors by providing direct, structured access to GSC’s API. This allows SEO professionals to instantly analyze search performance, indexing status, and CTR anomalies using conversational queries.

Main Features

1. Natural Language Query Engine: Translates plain English questions (e.g., “Top 10 keywords by clicks last month”) into precise GSC API requests. Uses schema mapping and intent recognition to parse complex queries, returning validated data tables instead of speculative text.
2. Multi-LLM Integration: Pre-configured compatibility with Claude, ChatGPT (via API), and Cursor IDE. Authenticates via OAuth 2.0 and syncs GSC property permissions, ensuring zero-code setup for connected platforms.
3. Real-Time URL Inspection: Directly checks Google’s index status, mobile usability, and crawl errors for any URL via the GSC API. Returns structured diagnostics (e.g., “Indexing: Blocked by noindex tag”) instead of raw JSON.
4. Sitemap API Orchestration: Automates sitemap submission, deletion, and coverage analysis. Monitors lastSubmitted dates and error ratios programmatically, triggering alerts for critical coverage drops.

Problems Solved

1. Pain Point: Manual CSV exports from GSC cause data staleness and LLM hallucinations due to format inconsistencies. Ekamoira MCP solves this with live API synchronization.
2. Target Audience: SEO analysts managing enterprise sites, agency technical directors, and content strategists requiring rapid GSC diagnostics.
3. Use Cases:
   • Diagnosing traffic drops by cross-filtering date ranges, devices, and countries via a single query.
   • Identifying high-impression/low-CTR pages for template optimization.
   • Auditing indexing coverage for new site migrations or CMS updates.

Unique Advantages

1. Differentiation: Unlike standalone SEO tools (e.g., SEMrush, Ahrefs), Ekamoira MCP leverages native GSC data without sampling. Contrasted with manual CSV uploads, it guarantees data freshness and eliminates hallucination risks.
2. Key Innovation: Proprietary query-to-API translator that normalizes GSC’s multi-dimensional data (queries, pages, devices, countries) into LLM-readable schemas. Uses parameter validation to prevent unsupported filter combinations.

Frequently Asked Questions (FAQ)

1. How does Ekamoira GSC MCP prevent AI hallucinations? It bypasses CSV uploads by routing natural language queries directly to Google’s Search Console API, ensuring responses reflect live, unaltered data.
2. Is my Google Search Console data secure with Ekamoira? Yes. The MCP uses OAuth 2.0 for read-only GSC access, adheres to GDPR/CCPA, and processes data via encrypted channels without storing raw logs.
3. Can I query historical GSC data beyond 16 months? No. Like the native GSC API, Ekamoira MCP accesses up to 16 months of historical performance data, aligning with Google’s data retention policies.
4. Does Ekamoira MCP support filtering by Google Discover or News results? Currently, it focuses on core web search metrics. Discover/News data requires separate GSC API endpoints not yet integrated.
5. How is this different from Google’s own GSC interface? It enables complex, cross-dimensional queries (e.g., “CTR by device for X pages”) via conversational language, bypassing manual filtering in the GSC UI.