Hosted MCP Server for GitHub
The GitHub MCP Server enables seamless integration between AI tools and GitHub, allowing automated workflows to manage repositories, issues, and pull requests d...
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AI
GitHub
+5
Capabilities
Host MCP Servers using FlowHunt
FlowHunt’s platform lets users create AI Agents for any service without the usual hassles of MCP servers. Host MCP servers for any service, automate workflows, and connect with enterprise data in seconds.
- Build AI Agents Visually
- Build AI Agents for BigQuery without MCP server complexity.
- MCP Server Hosting
- Host MCP servers for any service with easy integration.
- One-Click Auth
- Connect to Google BigQuery using secure Google Sign-in.
- Workflow Automation
- Automate SQL execution and data task management.
- Performance Analytics
- Use insights to enhance AI Agent performance.
Set Up Your BigQuery Environment
Connect via Google Sign-In
- Access FlowHunt: Log in to your FlowHunt.io dashboard .
- Navigate to Integrations: Find the “Integrations” section in the left sidebar.
- Select Google BigQuery: Click on the BigQuery integration option.
- Authenticate: Click the “Sign in with Google” button.
- Select the Google account associated with your Google Cloud Project.
- Grant FlowHunt the necessary permissions to access your BigQuery data.
💡 Note: Using Google Sign-in ensures that FlowHunt follows your existing Google Cloud IAM permissions, providing a secure and seamless connection without managing JSON keys.
Deploy the BigQuery MCP Server
Add the MCP Server
- Navigate to MCP Servers: Go to the “MCP Servers” tab in FlowHunt.
- Add New Server: Click “Add New MCP Server”.
- Select BigQuery: Choose “BigQuery MCP Server” from the list.
- Configure Tools: Select the specific tools you want your AI Agent to access.
MCP INTEGRATION
The following tools are available as part of the Google BigQuery MCP integration:
- bq_execute_query
Execute SQL queries (SELECT, INSERT, UPDATE, DELETE). Supports dry_run for validation.
- bq_list_datasets
List all BigQuery datasets available in your Google Cloud project.
- bq_get_dataset_info
Get metadata for a specific dataset, including location and description.
- bq_list_tables
List all tables and views within a specific BigQuery dataset.
- bq_get_table_info
Get detailed schema information, column types, and row counts for a table.
- bq_get_projects
List all Google Cloud projects accessible with your Google account.
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Connect MCP Server to Client
Get Your Configuration
- Access MCP Tab: Navigate to the “MCP” tab in your FlowHunt Dashboard.
- Select Server: Choose your BigQuery MCP server.
- Copy Configuration: Copy the JSON Configuration to connect your local AI tools or custom applications.
Create AI-Powered Data Workflows
Quick Start with Preconfigured Flow
- Template: In your MCP Server settings, click “Create Preconfigured Flow”.
- Setup: Choose the “Data Analyst Agent” template.
- Automate: Your agent can now browse schemas and write SQL to answer prompts like “Show me our top-selling products from the last 30 days.”
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List of Prompts
Try these practical prompts with your BigQuery-enabled AI Agent:
- Show me a list of all datasets in my project.
- What is the schema for the orders table in the ecommerce dataset?
- Run a dry run of a query that calculates total revenue for 2025.
- Summarize the top 5 customers by total spend from the sales table.
- Are there any tables in my project that contain PII or user_data in the name?
Conclusion
The Google BigQuery MCP Server on FlowHunt.io turns your data warehouse into an interactive resource for AI. With simple Google Sign-in and powerful SQL tools, you can automate reporting, audit schemas, and generate insights instantly.
Ready to start? Sign in with your Google account on FlowHunt and deploy your BigQuery MCP server today!
