Search. Scan. Stay Safe.
A comprehensive Model Context Protocol (MCP) server that provides access to FDA (Food and Drug Administration) data for Food safety information.
This MCP server offers 8 tools to access product safety data, helping users:
- Check product recalls and safety alerts for food products
- Monitor food safety issues and recall trends
- Analyze safety trends and company information
- Get comprehensive food safety insights
- Python 3.10 or higher
- pip or uv package manager
-
Clone or download the project:
git clone https://github.com/surabhya/SafetySearch.git cd SafetySearch
-
Install dependencies:
# Using pip pip install "mcp[cli]>=1.0.0" httpx>=0.24.0 pydantic>=2.0.0 # Or using uv (recommended) uv add "mcp[cli]>=1.0.0" httpx>=0.24.0 pydantic>=2.0.0
Note: If you have previously installed
mcp
in another project, or if you encounter errors likeFailed to spawn: mcp ... No such file or directory
, run:uv remove mcp uv add "mcp[cli]>=1.0.0"
This ensures the
mcp
binary is correctly linked to your current environment.
Test and validate the server using the MCP Inspector:
uv run mcp dev server.py
Run the server directly for testing:
uv run python server.py
Install the server in Claude Desktop for production use:
uv run mcp install server.py
Tool | Description | Parameters |
---|---|---|
search_recalls_by_product_description |
Searches for food recalls with detailed analysis, safety insights, and comprehensive reporting. | query: str |
search_recalls_by_product_type |
Searches for recalls by product type with detailed analysis, company trends, and safety recommendations. | product_type: str |
search_recalls_by_specific_product |
Checks for recalls on specific products with detailed safety information and recommendations. | product_name: str |
search_recalls_by_classification |
Searches for recalls by classification with detailed analysis and risk assessment. | classification: str |
search_recalls_by_code_info |
Searches for recalls by code info with detailed product tracking and safety alerts. | code_info: str |
search_recalls_by_date |
Searches for recalls by date range with detailed timeline analysis and safety trends. | days: int (default: 30) |
search_adverse_events_by_product |
Searches for adverse events with detailed case analysis and safety insights. | product_name: str |
get_symptom_summary_for_product |
Gets detailed symptom analysis, case details, and safety insights for a specific food product. | product_name: str |
The server is built with a simple, modular architecture designed for clarity and extensibility.
graph TD
subgraph "SafetySearch MCP"
A[User] -- "Tool Call" --> B["server.py<br/>(MCP Entrypoint)"];
B -- "Executes" --> C{"Food Tools<br/>(safetyscore/tools/food.py)"};
C -- "HTTP Request" --> D["API Client<br/>(safetyscore/api_client.py)"];
end
D -- "Calls" --> E["openFDA API<br/>(api.fda.gov)"];
subgraph "Testing Framework"
F[Pytest] -- "Runs" --> G["Test Suite<br/>(test_safetyscore/)"];
G -- "Tests" --> C;
end
server.py
: The main entry point of the MCP server. It initializes the toolsets and makes them available to the MCP environment.safetyscore/
: The core Python package containing all the logic.tools/
: This directory contains the different tool modules. Currently, it only containsfood.py
.food.py
: Implements the 8 tools for food safety, which provide detailed analysis and safety insights.
api_client.py
: A centralized asynchronous HTTP client for interacting with the external openFDA API. It handles request/response logic, error handling, and API key management.
test_safetyscore/
: Contains the test suite for the server, ensuring the reliability and correctness of the tools.
This structure separates concerns, making it easy to maintain and add new toolsets in the future.
Here are some examples of user prompts and the corresponding tool calls they would trigger.
-
User Prompt: "Are there any recalls for ice cream?"
food.search_recalls_by_product_description(query="ice cream")
-
User Prompt: "Show me recent recalls for bakery products."
food.search_recalls_by_product_type(product_type="Bakery")
-
User Prompt: "I bought some 'Ben & Jerry's Chocolate Fudge Brownie' ice cream, is it safe?"
food.search_recalls_by_specific_product(product_name="Ben & Jerry's Chocolate Fudge Brownie")
-
User Prompt: "List all the most serious food recalls."
food.search_recalls_by_classification(classification="Class I")
-
User Prompt: "The code on my food package is '222268'. Is there a recall for it?"
food.search_recalls_by_code_info(code_info="222268")
-
User Prompt: "What food recalls have happened in the last two weeks?"
food.search_recalls_by_date(days=14)
-
User Prompt: "I got sick after eating Cheerios. Have other people reported problems?"
food.search_adverse_events_by_product(product_name="Cheerios")
-
User Prompt: "What are the common symptoms people report after eating 'Lucky Charms'?"
food.get_symptom_summary_for_product(product_name="Lucky Charms")
To verify that all tools work as expected, you can run the provided test suites:
- Ensure you have installed all dependencies (see Installation section above)
From the project root directory, run:
# Test Food Tools
uv run python test_safetyscore/test_tools/test_food_tools.py
- Enforcement API:
https://api.fda.gov/food/enforcement.json
- Adverse Events API:
https://api.fda.gov/food/event.json
SafetySearch - Making FDA safety data accessible to everyone through the power of MCP.