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***LLM Integration with Firebolt** - Connect your AI assistants directly to your data warehouse
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- Enable AI agents to autonomously query your data and build analytics solutions
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- Provide LLMs with specialized knowledge of Firebolt's capabilities and features
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**LLM Integration with Firebolt**
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- Connect your AI assistants directly to your data warehouse
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- Enable AI agents to autonomously query data and generate insights
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- Provide LLMs with deep knowledge of Firebolt SQL, features, and documentation
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**SQL Query Execution**
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- Support for multiple query types and execution modes
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- Direct access to Firebolt databases
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**Documentation Access**
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- Grant LLMs access to comprehensive Firebolt docs, SQL reference, function lists, and more
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***SQL Query Execution**
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- Direct query execution against Firebolt databases
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- Support for multiple query types and execution modes
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**Account Management**
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***Documentation Access**
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- Comprehensive Firebolt documentation available to the LLM
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- SQL reference, function reference, and more
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- Seamless authentication with Firebolt service accounts
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- Connect to different engines and workspaces
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***Account Management**
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- Connect to different accounts and engines
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- Manage authentication seamlessly
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**Multi-platform Support**
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***Multi-platform Support**
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- Run on any platform supporting Go binaries
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- Docker container support for easy deployment
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- Runs anywhere Go binaries are supported
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- Official Docker image available for easy deployment
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## How To Use
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To get started with the Firebolt MCP Server, you'll need a Firebolt service account. If you don't have a Firebolt account yet, [sign up here](https://www.firebolt.io/signup).
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Before you start, ensure you have a Firebolt [service account](https://docs.firebolt.io/Guides/managing-your-organization/service-accounts.html) with a client ID and client secret.
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### Option 1: Use the Docker image
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### Installing the MCP Server
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You can run the Firebolt MCP Server either via Docker or by downloading the binary.
More details: [Claude MCP Quickstart Guide](https://modelcontextprotocol.io/quickstart/user)
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#### GitHub Copilot Chat (VSCode)
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To integrate MCP with Copilot Chat in VSCode, refer to the official documentation:
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## Requirements
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👉 [Extending Copilot Chat with the Model Context Protocol](https://docs.github.com/en/copilot/customizing-copilot/extending-copilot-chat-with-mcp)
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- Firebolt service account credentials (client ID and client secret)
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- For development: Go 1.24.1 or later
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- For deployment: Docker (optional)
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#### Cursor Editor
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To set up MCP in Cursor, follow their guide:
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👉 [Cursor Documentation on Model Context Protocol](https://docs.cursor.com/context/model-context-protocol)
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## Architecture
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The Firebolt MCP Server implements the [Model Context Protocol](https://github.com/anthropics/anthropic-cookbook/tree/main/model_context_protocol) specification, providing:
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Firebolt MCP Server implements the [Model Context Protocol](https://modelcontextprotocol.io/introduction), providing:
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1. **Tools** - Task-specific capabilities provided to the LLM:
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-`Connect`: Establish connections to Firebolt engines and databases
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-`Docs`: Access Firebolt documentation
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-`Query`: Execute SQL queries against Firebolt
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- `firebolt_docs`: Access Firebolt documentation
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- `firebolt_connect`: Establish connections to Firebolt engines and databases
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- `firebolt_query`: Execute SQL queries against Firebolt
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2. **Resources** - Data that can be referenced by the LLM:
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- Documentation articles
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- Account information
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- Database schema
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- Engine statistics
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- Documentation articles
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- Lists of Accounts, Databases, Engines
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3. **Prompts** - Predefined instructions for the LLM:
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- Firebolt Expert: Prompts the model to act as a Firebolt specialist
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- Firebolt Expert: Prompts the model to act as a Firebolt specialist
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