# Dremio MCP Server Architecture
## High Level Overview
The Dremio MCP Server implements the [Model Context Protocol (MCP)](https://modelcontextprotocol.io/introduction) to create a standardized interface between Large Language Models (LLMs) and Dremio data platform. This architecture enables seamless integration between LLMs and Dremio's capabilities, allowing for natural language interactions with data and analytics workflows.
### What is MCP?
At a glance, the MCP based architecture looks like this:
```mermaid
%%{init: { "themeVariables": { "fontFamily": "Inter" } } }%%
flowchart LR
subgraph "LLMs"
LLM["LLMs like Claude, etc.."]
end
subgraph "User's Server"
Host["Host with MCP Client<br/>(Claude desktop, IDEs, Agent)"]
S1["MCP Server A<br/>(for example..)"]
S2["Dremio MCP Server"]
Host <-->|"MCP Protocol"| S1
Host <-->|"MCP Protocol"| S2
Host <-->|"Interact with LLM. LLM calls<br/>tools from MCP server"| LLM
S1 <--> D1[("Local<br/>Data Source")]
end
subgraph "Remote Dremio cluster"
S2 <-->|"REST APIs<br/>Flight etc.."| D3[("Dremio")]
end
```
The architecture consists of three main components:
1. **LLM Layer**:
- Handles natural language understanding and generation
- Makes intelligent decisions about which tools to use
- Processes results and generates human-readable responses
2. **MCP Client/Host**:
- Provides the user interface (Claude desktop, IDEs, or other agents)
- Manages communication between LLMs and MCP servers
- Handles tool discovery and execution
3. **MCP Servers**:
- Dremio MCP Server: Provides specialized tools for Dremio interaction
- Other MCP Servers: Can run alongside Dremio MCP server for additional capabilities
- Each server exposes a standardized interface through the MCP protocol
## Interaction Flow
The following diagram illustrates the detailed interaction flow between components:
```mermaid
%%{init: { "themeVariables": { "fontFamily": "Inter" } } }%%
sequenceDiagram
participant User
box Claude desktop / LLM / Agent
participant Client as MCP Client / Frontend
participant LLM as Claude LLM
end
participant MCP as MCPServer
participant DB as Dremio
Note over Client,MCP: MCP server discovery and initialization
alt Client initializes MCP
Client->>MCP: List tools and prompt
MCP->>Client: Provides tools and prompt
end
Note over User,Client: What sales oriented tables do I have<br/>And what insights can you get from it
User->>Client: Submits natural languate question
Client->>LLM: Forwards question
loop Question requires relevant tools from MCP server
LLM->>Client: Requests tool execution - RunSQL
Client->>MCP: Sends tool call - RunSQL, GetSchemaOfTable
activate MCP
Note right of MCP: call tools one or more <br/> times to iterrogate catalog
MCP->>DB: Executes SQL query
activate DB
DB->>MCP: Provides results
deactivate DB
MCP-->>Client: Returns processed data
deactivate MCP
Client-->>LLM: Provides data
end
Note over Client,MCP: This process iterates as LLM processes<br/> data and asks for more tool invocations
LLM->>Client: Generates response
Client->>User: Delivers response
```
### Interaction Steps:
1. **Initialization Phase**:
- MCP Client discovers available MCP servers
- Each server provides its capabilities (tools) and prompts
- System establishes connections and validates access
2. **Query Processing**:
- User submits natural language questions
- LLM analyzes the question and determines required tools
- Tools are executed through the MCP protocol
- Results are processed and returned to the user
3. **Iterative Processing**:
- LLM may make multiple tool calls to gather complete information
- Each tool call is handled independently
- Results are accumulated and synthesized into final response
## Tool Discovery and Initialization
The following diagram shows how tools are discovered and initialized:
```mermaid
%%{init: { "themeVariables": { "fontFamily": "Inter" } } }%%
sequenceDiagram
box Claude desktop / LLM / Agent
participant LLM as Claude LLM
participant Client as MCP Client / Frontend
end
participant MCP as MCPServer
par Client to MCP
Client --> MCP: List available prompts
activate MCP
MCP --> Client: Returns prompts
deactivate MCP
and Client to MCP
Client --> MCP: List available tools
activate MCP
MCP --> Client: Returns tools, with arguments and description
deactivate MCP
end
```
### Tool Discovery Process:
1. **Prompt Discovery**:
- Client requests available prompts from MCP server
- Server returns specialized prompts for different use cases
- Prompts are cached for future use
2. **Tool Discovery**:
- Client requests available tools from MCP server
- Server returns tool definitions including:
- Tool names and descriptions
- Required arguments and types
- Expected return values
- Tools are registered with the LLM for use
This architecture enables flexible and extensible integration between LLMs and Dremio, allowing for natural language interaction with data while maintaining security and control through the MCP protocol.
