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Syne Ga Mcp
What is Syne Ga Mcp
syne_ga_mcp is a Model Context Protocol (MCP) server designed to interface with Google Analytics 4 (GA4) data, enabling AI assistants to query GA4 data through a standardized protocol.
Use cases
Use cases for syne_ga_mcp include generating custom reports for web traffic analysis, real-time monitoring of user engagement, and obtaining metadata for data-driven decision-making.
How to use
To use syne_ga_mcp, configure the server with Google service account credentials and utilize the MCP call_tool endpoint to run reports or retrieve metadata about GA4 properties.
Key features
Key features include the ability to run standard and real-time reports via the Google Analytics Data API v1beta, specify metrics and dimensions, and retrieve metadata about available metrics and dimensions for the configured GA4 property.
Where to use
syne_ga_mcp can be used in analytics and data reporting environments, particularly where Google Analytics 4 data needs to be accessed programmatically by AI applications or data analysis tools.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Overview
What is Syne Ga Mcp
syne_ga_mcp is a Model Context Protocol (MCP) server designed to interface with Google Analytics 4 (GA4) data, enabling AI assistants to query GA4 data through a standardized protocol.
Use cases
Use cases for syne_ga_mcp include generating custom reports for web traffic analysis, real-time monitoring of user engagement, and obtaining metadata for data-driven decision-making.
How to use
To use syne_ga_mcp, configure the server with Google service account credentials and utilize the MCP call_tool endpoint to run reports or retrieve metadata about GA4 properties.
Key features
Key features include the ability to run standard and real-time reports via the Google Analytics Data API v1beta, specify metrics and dimensions, and retrieve metadata about available metrics and dimensions for the configured GA4 property.
Where to use
syne_ga_mcp can be used in analytics and data reporting environments, particularly where Google Analytics 4 data needs to be accessed programmatically by AI applications or data analysis tools.
Clients Supporting MCP
The following are the main client software that supports the Model Context Protocol. Click the link to visit the official website for more information.
Content
Syne Google Analytics MCP Server
A Model Context Protocol (MCP) server for Google Analytics 4 data.
Overview
This server provides an MCP interface to Google Analytics 4 data, allowing AI assistants to query GA4 data through a standardized protocol.
Features
The server exposes the following tools via the MCP call_tool endpoint:
run_ga4_report: Runs a standard report using the Google Analytics Data API v1beta. Allows specifying metrics, optional dimensions, date range, and row limit.run_realtime_report: Runs a realtime report using the Google Analytics Data API v1beta. Allows specifying metrics, optional dimensions, and row limit.get_metadata: Gets metadata about available metrics and dimensions (or all) for the configured GA4 property.
It also handles authentication using Google service account credentials provided in the configuration.
tools = [
types.Tool(
name="run_ga4_report",
description="Runs a report using the Google Analytics Data API v1beta.",
inputSchema={
"type": "object",
"properties": {
"metrics": {
"type": "array",
"items": {"type": "string"},
"description": "Required. List of metric names (e.g., ['activeUsers', 'sessions']). See GA4 documentation for valid metrics."
},
"dimensions": {
"type": "array",
"items": {"type": "string"},
"description": "Optional. List of dimension names (e.g., ['country', 'city']). See GA4 documentation for valid dimensions.",
"optional": True
},
"date_range": {
"type": "string", # Could also be an object, handled by ga_handler
"description": "Optional. Date range alias ('today', 'yesterday', 'last7days', 'last30days') or an object like {'start_date': 'YYYY-MM-DD', 'end_date': 'YYYY-MM-DD'}.",
"default": "last30days"
},
"limit": {
"type": "integer",
"description": "Optional. The maximum number of rows to return in the report.",
"default": 10
}
},
"required": ["metrics"]
},
),
types.Tool(
name="run_realtime_report",
description="Runs a realtime report using the Google Analytics Data API v1beta.",
inputSchema={
"type": "object",
"properties": {
"metrics": {
"type": "array",
"items": {"type": "string"},
"description": "Required. List of metric names (e.g., ['activeUsers', 'screenPageViews']). See GA4 realtime documentation for valid metrics."
},
"dimensions": {
"type": "array",
"items": {"type": "string"},
"description": "Optional. List of dimension names (e.g., ['country', 'city']). See GA4 realtime documentation for valid dimensions.",
"optional": True
},
"limit": {
"type": "integer",
"description": "Optional. The maximum number of rows to return in the report.",
"default": 10
}
},
"required": ["metrics"]
},
),
types.Tool(
name="get_metadata",
description="Gets metadata about available metrics and dimensions for the configured property.",
inputSchema={
"type": "object",
"properties": {
"metadata_type": {
"type": "string",
"description": "Optional. Specifies the type of metadata to retrieve: 'metrics', 'dimensions', or 'all'.",
"default": "all",
"enum": ["metrics", "dimensions", "all"] # Adding enum for clarity
}
}
},
),
]
Dev Tools Supporting MCP
The following are the main code editors that support the Model Context Protocol. Click the link to visit the official website for more information.










