MCP server intelligence profile

Google Analytics MCP Server

Connects Google Analytics 4 data to Claude, Cursor and other MCP clients, enabling natural language queries of website traffic, user behavior, and analytics data with access to 200+ GA4 dimensions and metrics

Local Onlysurendranb
Awaiting current scanPypi · 2.11.3

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

1Distribution channel
10Independently observed tools
0Linked remote endpoints
AvailableVersion intelligence

Detailed security scan evidence is not public for this MCP yet. Public identity, registry metadata, and independently observed protocol inventory remain available.

Install and connect

Installation and connection instructions are shown only when supported by retained package, repository, or endpoint evidence.

Install google-analytics-mcp from PyPI

Install exact version 2.11.3. The executable name has not been verified, so it is intentionally not guessed.

python -m pip install 'google-analytics-mcp==2.11.3'

Identity

Canonical sluggoogle-analytics-mcp-server-9146925aDeploymentLocal Only
Canonical packagepypi:google-analytics-mcpRepositorysurendranb/google-analytics-mcp
First publishedAug 10, 2026Latest releaseAug 18, 2026
Last security verification—Classification confidence90%
PublicationDraftOfficial distributionNot verified

Distributions

ChannelIdentifierCurrent versionVersionsSource
pypigoogle-analytics-mcp2.11.33Repository

Current release

PackageVersionPublished / observedInventorySecurity scan
pypigoogle-analytics-mcp2.11.3CurrentAug 18, 202610 toolsSucceeded · 20 resources · 3 promptsEvidence restricted
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Current version evidence

No public current-version evidence is available yet.

Current protocol inventory

2025-06-18Negotiated protocol
Google Analytics 4Server-reported name
4Capability groups
Aug 18, 2026Observed

Tools 10

ToolCategoryAnnotationsRisk
get_dimensions_by_category Return all dimensions in a specific category with their API names and descriptions. Returns: {"dimension_api_name": "description", ...} The category name must exactly match a value returned by list_dimension_categories. Use search_schema instead if you already have a keyword — it is faster and more targeted than browsing by category. Args: category: Exact category name from list_dimension_categories (case-insensitive).
Input schema
{
  "properties": {
    "category": {
      "title": "Category",
      "type": "string"
    }
  },
  "required": [
    "category"
  ],
  "type": "object",
  "title": "get_dimensions_by_categoryArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
get_ga4_data Retrieve GA4 data with built-in intelligence for better and safer results. Returns on success: {"data": [...], "metadata": {...}, "_skills_tip": "..."}. For multi-row pulls (a time series like ['date'], or any breakdown) the result also carries "totals": {metric: value} — GA4 server-side aggregates across all rows. Read the period figure from "totals"; do NOT sum the rows yourself. (Additive metrics sum; rate metrics are period-computed by GA4.) Returns on volume warning: {"warning": "...", "estimated_rows": N, "suggestions": [...]} Returns on error: {"error": "..."} CRITICAL WORKFLOW — follow this sequence every time: 1. DISCOVER FIELDS: NEVER guess dimension or metric names. Call `search_schema`, `list_dimension_categories`, or `list_metric_categories` FIRST to verify exact API names for this property. Guessing costs you a failed round-trip. 2. DISCOVER PATTERN: For any domain-specific analysis, call `search_skills('<topic>')` BEFORE querying to get the proven methodology — correct dimensions, metrics, filters, and how to interpret the result. One extra call prevents multiple failures. Use for: traffic diagnosis, attribution, ecommerce, channel acquisition, content performance, geo/device segmentation, AI referrals, bot detection. 3. RETRIEVE: Call get_ga4_data with the verified fields and the skill's pattern. 4. TROUBLESHOOT: On schema error, invalid field, or filter parse error — do NOT retry by guessing. Your training may predate current GA4 (UA was sunset 2023-07-01). Call `search_schema('<keyword>')` to find the current name in THIS property, or `search_skills('ua-to-ga4' | 'common-metric-names' | 'filter-structures')` for the mapping. FIELD NAMES — GA4 API names vs common wrong guesses: - 'screenPageViews' not 'uniquePageviews' or 'pageViews' - 'totalUsers' not 'users' - 'keyEvents' not 'conversions' or 'goalCompletionsAll' - 'sessionKeyEventRate' not 'sessionConversionRate' or 'conversionRate' (GA4 renamed conversions→key events, 2024) - 'userEngagementDuration' not 'timeOnPage' or 'avgTimeOnPage' - 'averageSessionDuration' not 'avgSessionDuration' - 'itemsViewed' not 'itemViews' - 'ecommercePurchases' not 'purchases' - 'sessionDefaultChannelGroup' not 'sessionDefaultChannelGrouping' - 'sessionSource'/'sessionMedium' not 'source'/'medium' - All names are camelCase — never snake_case (page_path → pagePath, event_name → eventName) - 'bounceRate' and 'newUsers' are correct as-is DATE RANGES: - Format: 'YYYY-MM-DD' or relative strings: '7daysAgo', '30daysAgo', 'yesterday', 'today' - 'NdaysAgo' counts back from today, excluding today. 'yesterday' = last complete day. - Period comparison (YoY, WoW): run two separate queries with different date ranges, then compare the results. The API does not support multi-period in one call. SCOPE RULES — incompatible combinations return a 400 error: - Session dims (sessionSource, sessionMedium, sessionCampaignName) → use with sessions, bounceRate, sessionKeyEventRate. NOT with eventCount. - Event dims (eventName) → use with eventCount. NOT with sessions. - User dims (firstUserSource, firstUserMedium) → use with totalUsers, newUsers. NOT sessions. - Safe with any metric: date, deviceCategory, country, city, pagePath, pageTitle. FILTER STRUCTURE: - Simple: {"filter": {"fieldName": "sessionSource", "stringFilter": {"value": "google", "matchType": "CONTAINS"}}} - AND: {"andGroup": {"expressions": [{"filter": {...}}, {"filter": {...}}]}} - OR: {"orGroup": {"expressions": [{"filter": {...}}, {"filter": {...}}]}} - NOT: {"notExpression": {"filter": {...}}} - Wrong keys that break filters: and_filter→andGroup, or_filter→orGroup, not_filter→notExpression, filters→expressions, field→fieldName Args: dimensions: GA4 dimension names (verified via schema tools, e.g. ["date", "city"]). metrics: GA4 metric names (verified via schema tools, e.g. ["totalUsers", "sessions"]). date_range_start: Start date — 'YYYY-MM-DD' or '7daysAgo', '30daysAgo', 'yesterday'. date_range_end: End date — 'YYYY-MM-DD' or 'yesterday', 'today'. dimension_filter: Optional FilterExpression dict. camelCase and snake_case both accepted. limit: Max rows to return. Defaults to 1000. estimate_only: If True, returns only estimated row count without fetching data. proceed_with_large_dataset: Set True to bypass the 2500-row volume warning. enable_aggregation: If True, asks GA4 for server-side metric totals whenever a dimension splits the data across rows (e.g. a 7-day ['date'] pull), returned in a "totals" block so the model needn't sum rows. Default True. intent: Short plain-English description of what the user is trying to learn. E.g. "which channels drive most signups", "bot traffic audit for last month".
Input schema
{
  "properties": {
    "dimensions": {
      "default": [
        "date"
      ],
      "items": {
        "type": "string"
      },
      "title": "Dimensions",
      "type": "array"
    },
    "metrics": {
      "default": [
        "totalUsers",
        "newUsers",
        "sessions"
      ],
      "items": {
        "type": "string"
      },
      "title": "Metrics",
      "type": "array"
    },
    "date_range_start": {
      "default": "7daysAgo",
      "title": "Date Range Start",
      "type": "string"
    },
    "date_range_end": {
      "default": "yesterday",
      "title": "Date Range End",
      "type": "string"
    },
    "dimension_filter": {
      "additionalProperties": true,
      "default": null,
      "title": "Dimension Filter",
      "type": "object"
    },
    "limit": {
      "default": 1000,
      "title": "Limit",
      "type": "integer"
    },
    "estimate_only": {
      "default": false,
      "title": "Estimate Only",
      "type": "boolean"
    },
    "proceed_with_large_dataset": {
      "default": false,
      "title": "Proceed With Large Dataset",
      "type": "boolean"
    },
    "enable_aggregation": {
      "default": true,
      "title": "Enable Aggregation",
      "type": "boolean"
    },
    "intent": {
      "default": null,
      "title": "Intent",
      "type": "string"
    }
  },
  "type": "object",
  "title": "get_ga4_dataArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": true,
  "readOnlyHint": true
}
—Read onlyIdempotentOpen world—
get_metrics_by_category Return all metrics in a specific category with their API names and descriptions. Returns: {"metric_api_name": "description", ...} The category name must exactly match a value returned by list_metric_categories. Use search_schema instead if you already have a keyword — it is faster and more targeted than browsing by category. Args: category: Exact category name from list_metric_categories (case-insensitive).
Input schema
{
  "properties": {
    "category": {
      "title": "Category",
      "type": "string"
    }
  },
  "required": [
    "category"
  ],
  "type": "object",
  "title": "get_metrics_by_categoryArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
get_property_schema Returns the complete schema for the configured GA4 property, including all available dimensions and metrics (standard and custom). Warning: This can be a very large object (10k+ tokens). Use search_schema for most discovery tasks.
Input schema
{
  "properties": {},
  "type": "object",
  "title": "get_property_schemaArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
get_troubleshooting_guide Returns the troubleshooting/setup guide for a topic, served from inside the server (no network needed). Use whenever you hit a schema error, dimension_filter parse error, IAM / 403 authorization error, or a boot-time setup error. Args: topic: One of "setup", "iam", or "schema".
Input schema
{
  "properties": {
    "topic": {
      "title": "Topic",
      "type": "string"
    }
  },
  "required": [
    "topic"
  ],
  "type": "object",
  "title": "get_troubleshooting_guideArguments"
}
Output schema
{
  "properties": {
    "result": {
      "title": "Result",
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "type": "object",
  "title": "get_troubleshooting_guideOutput"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
list_dimension_categories List all dimension categories for this GA4 property, with a count of dimensions in each category. Returns: {"dimension_categories": {"Category Name": count, ...}} Use this as the first step in dimension exploration — browse categories, then call get_dimensions_by_category with the name that fits your analysis. Use search_schema instead if you already have a keyword to search for.
Input schema
{
  "properties": {},
  "type": "object",
  "title": "list_dimension_categoriesArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
list_metric_categories List all metric categories for this GA4 property, with a count of metrics in each category. Returns: {"metric_categories": {"Category Name": count, ...}} Use this as the first step in metric exploration — browse categories, then call get_metrics_by_category with the name that fits your analysis. Use search_schema instead if you already have a keyword to search for.
Input schema
{
  "properties": {},
  "type": "object",
  "title": "list_metric_categoriesArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
search_schema Search for a keyword across all dimensions and metrics for this property. Returns a ranked list of up to 10 matching fields scored by relevance. Returns: {"top_results": {"DIMENSION: api_name": score, "METRIC: api_name": score, ...}} Use this when you have a concept ("engagement", "revenue", "channel") and need exact API field names before calling get_ga4_data. Use list_dimension_categories or list_metric_categories instead if you want to browse all available fields without a specific keyword. Args: keyword: One or more keywords to search for (e.g., "user", "campaign revenue").
Input schema
{
  "properties": {
    "keyword": {
      "title": "Keyword",
      "type": "string"
    }
  },
  "required": [
    "keyword"
  ],
  "type": "object",
  "title": "search_schemaArguments"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": false,
  "readOnlyHint": true
}
—Read onlyIdempotentClosed world—
search_skills Fetch analytical recipes and how-to guides from the GA4 skills library. Skills are domain-specific playbooks for common GA4 analysis patterns — exact dimensions, metrics, filters, and interpretation logic for each use case. Call this BEFORE querying get_ga4_data for any domain-specific analysis. Available skills: traffic-diagnosis, attribution-scope, channel-acquisition, content-performance, geo-device-segmentation, ecommerce-analysis, ai-referral-analysis, bot-traffic-detection, common-metric-names, filter-structures, custom-dimensions, compatible-combinations, ua-to-ga4, date-ranges, ga4-limitations. Usage: - search_skills("") → returns full index of all skills - search_skills("ecommerce") → returns the ecommerce-analysis skill - search_skills("ua-to-ga4") → returns the UA→GA4 field name mapping Args: query: A skill name (exact slug) or empty string to browse the full index.
Input schema
{
  "properties": {
    "query": {
      "title": "Query",
      "type": "string"
    }
  },
  "required": [
    "query"
  ],
  "type": "object",
  "title": "search_skillsArguments"
}
Output schema
{
  "properties": {
    "result": {
      "title": "Result",
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "type": "object",
  "title": "search_skillsOutput"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": true,
  "readOnlyHint": true
}
—Read onlyIdempotentOpen world—
setup_ga4_access Interactively fix a broken GA4 MCP setup (missing property ID, missing or expired credentials, or missing GA4 access) by asking the user for the needed input through the client, then re-initializing without a restart. Call this whenever a configuration or authentication error is reported.
Input schema
{
  "properties": {},
  "type": "object",
  "title": "setup_ga4_accessArguments"
}
Output schema
{
  "properties": {
    "result": {
      "title": "Result",
      "type": "string"
    }
  },
  "required": [
    "result"
  ],
  "type": "object",
  "title": "setup_ga4_accessOutput"
}
Annotations
{
  "idempotentHint": true,
  "openWorldHint": true,
  "readOnlyHint": true
}
—Read onlyIdempotentOpen world—

Resources 20

  • get_fix_iamdocs://fix/iam
  • get_fix_schemadocs://fix/schema
  • get_fix_setupdocs://fix/setup
  • get_setup_guidedocs://setup_guide

    Provides instructions to the agent on how to heal the human's MCP setup.

  • skill-ai-referral-analysisskill://ai-referral-analysis

    GA4 analytical skill 'ai-referral-analysis' — the same recipe served by search_skills('ai-referral-analysis'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-attribution-scopeskill://attribution-scope

    GA4 analytical skill 'attribution-scope' — the same recipe served by search_skills('attribution-scope'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-bot-traffic-detectionskill://bot-traffic-detection

    GA4 analytical skill 'bot-traffic-detection' — the same recipe served by search_skills('bot-traffic-detection'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-channel-acquisitionskill://channel-acquisition

    GA4 analytical skill 'channel-acquisition' — the same recipe served by search_skills('channel-acquisition'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-common-metric-namesskill://common-metric-names

    GA4 analytical skill 'common-metric-names' — the same recipe served by search_skills('common-metric-names'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-compatible-combinationsskill://compatible-combinations

    GA4 analytical skill 'compatible-combinations' — the same recipe served by search_skills('compatible-combinations'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-content-performanceskill://content-performance

    GA4 analytical skill 'content-performance' — the same recipe served by search_skills('content-performance'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-custom-dimensionsskill://custom-dimensions

    GA4 analytical skill 'custom-dimensions' — the same recipe served by search_skills('custom-dimensions'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-date-rangesskill://date-ranges

    GA4 analytical skill 'date-ranges' — the same recipe served by search_skills('date-ranges'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-ecommerce-analysisskill://ecommerce-analysis

    GA4 analytical skill 'ecommerce-analysis' — the same recipe served by search_skills('ecommerce-analysis'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-filter-structuresskill://filter-structures

    GA4 analytical skill 'filter-structures' — the same recipe served by search_skills('filter-structures'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-ga4-limitationsskill://ga4-limitations

    GA4 analytical skill 'ga4-limitations' — the same recipe served by search_skills('ga4-limitations'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-geo-device-segmentationskill://geo-device-segmentation

    GA4 analytical skill 'geo-device-segmentation' — the same recipe served by search_skills('geo-device-segmentation'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-indexskill://index

    GA4 analytical skill 'index' — the same recipe served by search_skills('index'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-traffic-diagnosisskill://traffic-diagnosis

    GA4 analytical skill 'traffic-diagnosis' — the same recipe served by search_skills('traffic-diagnosis'): proven dimensions, metrics, filters, and how to interpret the result.

  • skill-ua-to-ga4skill://ua-to-ga4

    GA4 analytical skill 'ua-to-ga4' — the same recipe served by search_skills('ua-to-ga4'): proven dimensions, metrics, filters, and how to interpret the result.

Resource templates 0

  • None observed.

Prompts 3

  • explain-my-traffic-dropexplain-my-traffic-drop

    Diagnose why traffic fell: isolate the drop by channel, source, page, geo, and device using the traffic-diagnosis methodology.

  • find-whats-brokenfind-whats-broken

    Triage a GA4 MCP setup or configuration problem: pinpoint the exact blocker (credentials, property ID, IAM, expired auth) and fix it.

  • traffic-deep-divetraffic-deep-dive

    Full GA4 traffic review for a period: volume, channels, content, geo/devices — using the server's proven query patterns.

Remote endpoints

EndpointTransportAuthenticationHealthObserved
No verified remote endpoint is linked.

Google Analytics MCP Server questions

How do I install Google Analytics MCP Server?

Install the selected package version with: python -m pip install 'google-analytics-mcp==2.11.3'

What tools does Google Analytics MCP Server provide?

Google Analytics MCP Server exposed 10 tools during independent protocol observation, including get_dimensions_by_category, get_ga4_data, get_metrics_by_category, get_property_schema, get_troubleshooting_guide, list_dimension_categories, list_metric_categories, search_schema, and others.

Is Google Analytics MCP Server secure?

The selected current version does not yet have completed public verification. Unknown does not mean clean or vulnerable.

Company and product intelligence

These internal links are derived from strong identity fields such as the implementation name, package, repository, vendor, and listing name—not generic description prose.

Associated company landscape

Google intelligence →

Association is based on retained identity fields; it does not by itself prove first-party publication.

Google 917 matches

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