open-index/open-npm huggingface dataset:
npm package: @iflow-mcp/datagov-mcp-server
Description: An MCP server for accessing data from Data.gov, providing tools and resources for interacting with government datasets.
Author: Joao Bondan
Latest version: 0.1.1

# Data.gov MCP Server

An MCP server for accessing data from Data.gov, providing tools and resources for interacting with government datasets.

<a href="https://glama.ai/mcp/servers/qi5i2d6sen">
  <img width="380" height="200" src="https://glama.ai/mcp/servers/qi5i2d6sen/badge" alt="Data.gov Server MCP server" />
</a>

## Installation

1.  **Install the package globally:**

    ```bash
    npm install -g @melaodoidao/datagov-mcp-server
    ```

2. **Configure the MCP Server:**

   - Add the following entry to your `cline_mcp_settings.json` file (usually located in `~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/` on macOS):

     ```json
      {
        "mcpServers": {
          "datagov": {
            "command": "datagov-mcp-server",
            "args": [],
            "env": {}
          }
        }
      }
     ```
    - If you are using the Claude Desktop app, add the entry to `~/Library/Application Support/Claude/claude_desktop_config.json` instead.

## Usage

This server provides the following tools:

*   `package_search`: Search for packages (datasets) on Data.gov.
*   `package_show`: Get details for a specific package (dataset).
*   `group_list`: List groups on Data.gov.
*   `tag_list`: List tags on Data.gov.

It also provides the following resource template:

*   `datagov://resource/{url}`: Access a Data.gov resource by its URL.

You can use these tools and resources with Cline by specifying the server name (`datagov-mcp-server`) and the tool/resource name.

## Contributing

Contributions are welcome! Please feel free to submit issues or pull requests.

## License

MIT License
npm package: @iflow-mcp/dbt-semantic-layer-mcp-server
Description: MCP server for using the DBT Semantic Layer API
Author: TommyBez
Latest version: 0.1.3

# dbt Semantic Layer MCP Server

[![smithery badge](https://smithery.ai/badge/@TommyBez/dbt-semantic-layer-mcp)](https://smithery.ai/server/@TommyBez/dbt-semantic-layer-mcp)

A Model-Connector-Presenter (MCP) server for seamlessly querying the dbt Semantic Layer through Claude Desktop and other compatible AI assistants.

## What is the dbt Semantic Layer?

The [dbt Semantic Layer](https://docs.getdbt.com/docs/use-dbt-semantic-layer/dbt-sl) is a powerful feature that allows you to define metrics once in your dbt project and reuse them consistently across your entire data stack. It provides:

- A single source of truth for business metrics
- Consistent metric definitions across all data tools
- Simplified access to complex metrics for all team members

## About This Project

This MCP server acts as a bridge between AI assistants (like Claude) and the dbt Semantic Layer, enabling you to:

- Query metrics directly through natural language conversations
- Explore available metrics and their definitions
- Analyze data with dimensional breakdowns and filters
- Visualize results within your AI assistant interface

## Features

- 🔍 **Metric Discovery**: Browse and search available metrics in your dbt Semantic Layer
- 📊 **Query Creation**: Generate and execute semantic queries through natural language
- 🧮 **Data Analysis**: Filter, group, and order metrics for deeper insights
- 📈 **Result Visualization**: Display query results in an easy-to-understand format

## Prerequisites

- A dbt Cloud account with Semantic Layer enabled
- API access to your dbt Cloud instance
- Node.js (v14 or later)

## Installation

### Via Smithery (Recommended)

The easiest way to install is via [Smithery](https://smithery.ai/server/@TommyBez/dbt-semantic-layer-mcp):

```bash
npx -y @smithery/cli install @TommyBez/dbt-semantic-layer-mcp --client claude
```

## Usage

Once installed and configured, you can interact with the dbt Semantic Layer directly from Claude Desktop:

1. Ask about available metrics: "What metrics are available in my dbt Semantic Layer?"
2. Query specific metrics: "Show me monthly revenue for the last quarter grouped by product category"
3. Analyze trends: "What's the week-over-week growth in user signups?"

## Troubleshooting

If you encounter issues:

- Verify your API credentials are correct
- Ensure your dbt Cloud project has Semantic Layer enabled
- Check that your metrics are properly defined in your dbt project

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the LICENSE file for details.

## Acknowledgments

- [dbt Labs](https://www.getdbt.com/) for creating the dbt Semantic Layer
- [Smithery](https://smithery.ai/) for the MCP deployment platform
- [LiteMCP](https://github.com/wong2/litemcp) for the MCP development package