HAL
HAL is an MCP server that provides HTTP API capabilities for large language models, supporting network requests through a secure interface and automatic generation of tools from OpenAPI specifications.
rating : 2.5 points
downloads : 5.6K
What is HAL?
HAL is a Model Context Protocol (MCP) server specifically designed for large language models (LLMs), enabling them to securely interact with various Web APIs via the HTTP protocol. It acts like an intelligent API gateway, allowing AI models to access various services on the Internet.How to use HAL?
Using HAL is very simple. Just install it via npm and configure the MCP client. HAL will automatically handle API requests, including authentication, parameter passing, and result return, allowing AI models to focus on business logic.Use cases
HAL is very suitable for scenarios where AI models need to access external APIs, such as: getting real - time data, submitting forms, calling cloud services, integrating third - party APIs, etc. It is particularly suitable for building AI assistants, automated workflows, and intelligent application integrations.Main features
Full support for HTTP methods
Supports all HTTP methods such as GET, POST, PUT, PATCH, DELETE, OPTIONS, and HEAD, meeting various API call requirements.
Secure key management
Manages sensitive information such as API keys through environment variables, uses the {secrets.key} template for secure replacement, and automatically masks sensitive data in responses.
OpenAPI/Swagger integration
Automatically generates API tools from OpenAPI specifications, allowing the use of hundreds of API endpoints without manual coding.
URL filtering
Controls accessible API endpoints through whitelist and blacklist mechanisms to enhance security.
Built - in documentation
Automatically generates API documentation for easy querying of available functions and parameters.
Advantages
Secure isolation: Executes API calls in a controlled environment to protect the main system's security.
Ease of use: Simple configuration allows AI models to access hundreds of APIs.
Flexibility: Supports custom request headers and request bodies to adapt to various API specifications.
Automation: Automatically generates tools from OpenAPI specifications, reducing manual work.
Cross - platform: Based on Node.js, it can run on various operating systems.
Limitations
Performance overhead: Each API call needs to be relayed through HAL.
Learning curve: Requires understanding of basic concepts of HTTP API and OpenAPI specifications.
Dependence on external services: API availability depends on the stability of third - party services.
How to use
Install HAL
Install the HAL MCP server globally via npm.
Configure the MCP client
Add the HAL server to your MCP client configuration.
Set environment variables
Configure sensitive information such as API keys as environment variables.
Start the service
Start the MCP client, and HAL will run automatically.
Start using
Your AI model can now access the configured APIs through HAL.
Usage examples
Get GitHub user information
Get the basic information of a specified user through the GitHub API.
Query weather data
Query the weather conditions of a specified city through the OpenWeatherMap API.
Submit form data
Submit new contact information to the CRM system.
Frequently Asked Questions
Which HTTP methods does HAL support?
How to protect my API keys from being leaked?
Can HAL handle API rate limits?
How to view the API documentation generated by HAL?
Does HAL support WebSocket?
Related resources
Full documentation
Detailed usage guide and API reference for HAL.
GitHub repository
Source code and issue tracking for HAL.
Introduction to the MCP protocol
Official documentation for the Model Context Protocol.
OpenAPI specification
Official documentation for the OpenAPI/Swagger specification.

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