mcp_agribalyse

# mcp-server-agribalyse 🌿 **A Model Context Protocol (MCP) server for querying the ADEME Agribalyse 3.1 dataset.** This MCP server provides tools and resources to interact with the Agribalyse public API, enabling Large Language Models to retrieve and analyze environmental impact data on food products. > ⚠️ Note: This server is based on the [FastMCP](https://github.com/modelcontextprotocol) framework and is actively maintained. API coverage may evolve. --- ## 🚀 Overview Agribalyse is a dataset published by ADEME, offering environmental indicators (climate impact, water use, ecotoxicity, etc.) for thousands of food products. This MCP server allows LLMs to: - Search food product data. - Aggregate environmental metrics. - List possible filter values. - Understand dataset structure. --- ## 🧰 Tools | Tool Name | Description | |------------------------|-------------------------------------------------------------| | `read_lines` | Query rows from the Agribalyse dataset | | `get_values` | Get distinct values for a given text field | | `get_metric_agg` | Compute a single metric (avg, min, etc.) on a numeric field | | `get_simple_metrics_agg` | Compute metrics on one or more fields at once | | `get_words_agg` | Retrieve most frequent tokens in a text field | | `read_schema` | Get the complete column schema of the dataset | | `read_safe_schema` | Get a reduced version of the column schema | | `read_api_docs` | Fetch the full OpenAPI specification from the ADEME API | --- ## 📚 Resources | URI | Description | |------------------------------------|-------------------------------------------------------| | `agribalyse://fields` | List of allowed text fields for querying | | `agribalyse://files` | Available data files published by ADEME | | `agribalyse://sample-lines` | A sample of dataset rows | | `agribalyse://columns/sortables` | Fields that can be used for sorting | | `agribalyse://metrics/fields` | Numeric fields usable for aggregation | | `agribalyse://metrics/types` | Supported metric types (avg, sum, percentiles, etc.) | | `agribalyse://fields/descriptions` | Human-readable descriptions of each dataset column | --- ## 💬 Prompts This server also includes predefined prompts for easier interaction: - `search_product`: Ask for environmental info about a named product - `ask_stat`: Ask for a specific metric on an indicator - `compare_products`: Compare two products by one indicator - `list_field_values`: List possible values of a given field - `sample_prompt`: Ask to preview sample data - `explain_indicator`: Ask for an explanation of an indicator - `custom_query_prompt`: Prompt chain for guided query refinement --- ## 🧪 Debugging You can inspect server behavior using: ``` npx @modelcontextprotocol/inspector uvx run src/agribalyse/server.py ``` Or follow logs using: ``` mcp dev server.py ``` ## 🧑‍💻 Client Example To test the MCP server using a client, an example client implementation using OpenAI is provided. Run the client with: ``` python client/client.py ``` This will execute example prompts and display the server responses, allowing you to observe how the MCP server handles requests. ## 🧪 Running Tests To run the test suite using pytest, make sure your virtual environment is activated and then run: ``` pytest tests/test_mcp_tools ``` This will execute all unit tests and validate the MCP tools integration. ## 👩‍💻 Maintainer **Author**: Tracy André **Organization**: Positive Solutions **Contact**: tracy.andre@food-pilot.eu