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MCP server for Apache Gravitino(incubating)

MCP server for Apache Gravitino(incubating)

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github.com/datastratoDatabases23Updated 69w ago

About MCP server for Apache Gravitino(incubating)

MCP server for Apache Gravitino is an MCP server built on FastMCP that exposes metadata operations for Apache Gravitino through tools. It covers catalogs, schemas, tables, models, users, tags and roles, and suits users who want an AI assistant to query or manage metadata.

Key features

  1. 01Catalog, schema and table metadata queries
  2. 02Tag association with tables and columns
  3. 03Granting and revoking user roles
  4. 04Model and model version lookup
  5. 05Token and basic authentication support

Use cases

  1. 01Asking an AI assistant about table structures and columns
  2. 02Finding data objects by tag
  3. 03Managing role assignments for users

MCP support

The project runs as an MCP server and provides a selected set of Gravitino metadata tools to MCP clients. Enabled tools can be limited with the GRAVITINO_ACTIVE_TOOLS setting.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Server for Apache Gravitino

Python Version

MCP server providing Gravitino APIs - A FastMCP integration for Apache Gravitino services.

Features

  • Seamless integration with FastMCP for Gravitino APIs
  • Simplified interface for metadata interaction
  • Supports metadata operations for catalogs, schemas, tables, models, users, tags, and user-role management

Installation

This project uses uv as the dependency and virtual environment management tool. Please ensure uv is installed on your system.

  1. Clone the repository:

    git clone [email protected]:datastrato/mcp-server-gravitino.git
    
  2. Navigate into the project directory:

    cd mcp-server-gravitino
    
  3. Create a virtual environment:

    uv venv
    
  4. Activate the virtual environment:

    source .venv/bin/activate
    
  5. Install dependencies:

    uv install
    

Configuration

Common Configuration

Regardless of the Authorization, the following environment variables need to be set:

GRAVITINO_METALAKE=<YOUR_METALAKE> # default: "metalake_demo"
GRAVITINO_URI=<YOUR_GRAVITINO_URI>
  • GRAVITINO_URI: The base URL of your Gravitino server.
  • GRAVITINO_METALAKE: The name of the metakube to use.
Authorization

mcp-server-gravitino supports both token-based and basic authentication methods. These mechanisms allow secure access to MCP tools and prompts and are suitable for integration with external systems.

Token Authentication

Set the following environment variables:

GRAVITINO_JWT_TOKEN=<YOUR_GRAVITINO_JWT_TOKEN>

GRAVITINO_JWT_TOKEN: The JWT token for authentication.

Basic Authentication

Alternatively, you can use basic authentication:

GRAVITINO_USERNAME=<YOUR_GRAVITINO_USERNAME>
GRAVITINO_PASSWORD=<YOUR_GRAVITINO_PASSWORD>
  • GRAVITINO_USERNAME: The username for Gravitino authentication.
  • GRAVITINO_PASSWORD: The corresponding password.
Tool Activation

Tool activation is currently based on method names (e.g., get_list_of_table). You can specify which tools to activate by setting the optional environment variable GRAVITINO_ACTIVE_TOOLS. The default value is *, which activates all tools. If just want to activate get_list_of_roles tool, you can set the environment variable as follows:

GRAVITINO_ACTIVE_TOOLS=get_list_of_roles

Usage

To launch the Gravitino MCP Server, run the following command:

uv \
--directory /path/to/mcp-gravitino \
run \
--with fastmcp \
--with httpx \
--with mcp-server-gravitino \
python -m mcp_server_gravitino.server

The meaning of each argument is as follows:

ArgumentDescription
uvLaunches the UV CLI tool
--directory /path/to/mcp-gravitinoSpecifies the working project directory with pyproject.toml
runIndicates that a command will be executed in the managed environment
--with fastmcpAdds fastmcp to the runtime environment without altering project deps
--with httpxAdds httpx dependency for async HTTP functionality
--with mcp-server-gravitinoAdds the local module as a runtime dependency
python -m mcp_server_gravitino.serverStarts the MCP server using the package's entry module
Goose Client Example

Example configuration to run the server using Goose:

{
  "mcpServers": {
    "Gravitino": {
      "command": "uv",
      "args": [
        "--directory",
        "/Users/user/workspace/mcp-server-gravitino",
        "run",
        "--with",
        "fastmcp",
        "--with",
        "httpx",
        "--with",
        "mcp-server-gravitino",
        "python",
        "-m",
        "mcp_server_gravitino.server"
      ],
      "env": {
        "GRAVITINO_URI": "http://localhost:8090",
        "GRAVITINO_USERNAME": "admin",
        "GRAVITINO_PASSWORD": "admin",
        "GRAVITINO_METALAKE": "metalake_demo"
      }
    }
  }
}

Tool List

mcp-server-gravitino does not expose all Gravitino APIs, but provides a selected set of optimized tools:

Table Tools
  • get_list_of_catalogs: Retrieve a list of catalogs
  • get_list_of_schemas: Retrieve a list of schemas
  • get_list_of_tables: Retrieve a paginated list of tables
  • get_table_by_fqn: Fetch detailed information for a specific table
  • get_table_columns_by_fqn: Retrieve column information for a table
Tag Tools
  • get_list_of_tags: Retrieve all tags
  • associate_tag_to_entity: Attach a tag to a table or column
  • list_objects_by_tag: List objects associated with a specific tag
User Role Tools
  • get_list_of_roles: Retrieve all roles
  • get_list_of_users: Retrieve all users
  • grant_role_to_user: Assign a role to a user
  • revoke_role_from_user: Revoke a user's role
Model Tools
  • get_list_of_models: Retrieve a list of models
  • get_list_of_model_versions_by_fqn: Get versions of a model by fully qualified name

Each tool is designed to return concise and relevant metadata to stay within LLM token limits while maintaining semantic integrity.

License

This project is licensed under the Apache License Version 2.0.

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