Axiom MCP Server: Universal Adapter for AI Application Integration

Overview: What is Axiom MCP Server?

Axiom MCP Server, a JavaScript port of the original Go version, serves as an essential bridge between AI applications and data sources through Model Context Protocol (MCP). This server enables advanced AI applications like Claude Desktop, Continue, Cursor, and more to seamlessly query data using Axiom Processing Language (APL), ensuring efficient and reliable data retrieval for complex workflows. The implementation is designed with developers in mind, providing a robust platform that enhances the capabilities of AI applications by standardizing their interaction with datasets and tools.

🔧 Core Features & MCP Capabilities

Axiom MCP Server leverages Model Context Protocol to offer a rich set of features tailored for AI application integration. By adhering closely to the MCP specifications, it ensures compatibility across various AI clients while providing detailed control over queries and data access rates. The server supports real-time query execution, dataset listing functionalities, and custom environment configurations, making it highly adaptable to diverse use cases.

The core capabilities include:

• Query Execution: Execute APL queries to fetch specific data subsets.
• Dataset Management: List available datasets for context-aware operations.
• Rate Limiting: Manage the rate of requests and burst capacity to ensure stable performance.
• Custom Configuration: Allow for flexible environment setup via config files or CLI options.

These features make Axiom MCP Server an indispensable tool in AI workflows, streamlining interactions between complex applications and data sources.

⚙️ MCP Architecture & Protocol Implementation

The architecture of Axiom MCP Server is designed to integrate seamlessly with the Model Context Protocol. It follows a client-server model where the server acts as the intermediary for AI applications to query data from various data sources. The protocol flow ensures that all communications occur efficiently and securely, managing API key authentication and rate limiting transparently.

The architecture includes:

• Client-Side MCP Client: An interface through which AI applications interact with the server.
• Server-Side Implementation: The node.js npm module enabling easy integration into Node.js environments.
• Data Source Interaction: Handles direct connection to external data sources based on given parameters.

This design ensures a standardized and efficient interaction model, reducing development complexity for integrating multiple tools and data sources into AI applications.

🚀 Getting Started with Installation

MCP Configuration

To get started with Axiom MCP Server, you need to set up the necessary environment configurations. The server can be run using npm or configured via a custom JSON file. Below are detailed steps for both approaches:

Using Environment Variables

Install the package globally:

npm install -g mcp-server-axiom

Configure your environment variables in a .env file:

AXIOM_TOKEN=your_token_here
AXIOM_ORG_ID=your_org_id_here
AXIOM_URL=https://api.axiom.co  # Optional, defaults to https://api.axiom.co
PORT=3000                         # Optional, default is 3000

Run the server:

mcp-server-axiom

Using a Config File

Create and configure config.json with your API token and other settings:

{
  "token": "your_token_here",
  "url": "https://custom.axiom.co", // Optional, default is https://api.axiom.co
  "orgId": "your_org_id_here",
  "queryRate": 2,
  "queryBurst": 5,
  "datasetsRate": 1,
  "datasetsBurst": 2
}

Run the server with the configuration file:

mcp-server-axiom config.json

💡 Key Use Cases in AI Workflows

Axiom MCP Server finds extensive use in a variety of AI workflows. Here are two realistic scenarios illustrating its application:

1. Fraud Detection Analysis: In this scenario, an AI fraud detection system requires real-time access to transactional logs and customer data. Axiom MCP Server can be configured to fetch relevant transaction details based on predefined APL queries. For instance:

   curl -X POST http://localhost:3000/tools/queryApl/call \
     -H "Content-Type: application/json" \
     -d '{
       "arguments": {
         "query": "['logs'] | where ['amount'] > 10000"
       }
     }'
   

2. Customer Support Chatbot Integration: A chatbot needs to retrieve customer history and service records from a database to provide contextual responses. Using MCP, the server can efficiently list available datasets:

   curl -X POST http://localhost:3000/tools/listDatasets/call \
     -H "Content-Type: application/json" \
     -d '{
       "arguments": {}
     }'
   

These use cases showcase how Axiom MCP Server can be integrated into complex AI workflows to deliver more efficient and data-driven solutions.

🔌 Integration with MCP Clients

Axiom MCP Server supports a wide range of MCP clients, ensuring compatibility across various AI applications:

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅		Full Support
Cursor	❌	✅	❌	Tools Only

This matrix highlights the comprehensive support for query tools and prompts, making Axiom MCP Server a versatile choice for integrating AI applications.

📊 Performance & Compatibility Matrix

To ensure robust performance, Axiom MCP Server is designed with configurable rate limiting to manage query bursts. The following table provides an overview of its compatibility and performance metrics:

Configuration Parameter	Default Value	Description
AXIOM_QUERY_RATE	1	Queries per second limit for APL execution (default is 1)
AXIOM_QUERY_BURST	1	Query burst capacity (default is 1)
AXIOM_DATASETS_RATE	1	Dataset list operations per second (default is 1)
AXIOM_DATASETS_BURST	1	Dataset list burst capacity (default is 1)

These settings can be adjusted based on the specific requirements of your AI application.

🛠️ Advanced Configuration & Security

For advanced users, Axiom MCP Server offers several configuration options to tailor its behavior. Key configurations include:

• API Token: An essential security measure controlling access.
• Rate Limiting Settings: Configurable limits for queries and dataset operations to prevent overloading the server.
• Custom Port Binding: Allows running the server on a non-standard port.

Example Configuration Code

Here’s an example of how to configure environment variables in detail:

{
  "api": {
    "token": "your_token",
    "url": "https://custom.axiom.co",   // Custom API URL (default: https://api.axiom.co)
    "orgId": "your_org_id",
    "queryRate": 2,         // Queries per second limit
    "queryBurst": 5,        // Query burst capacity
    "datasetsRate": 1,      // Dataset list operations per second
    "datasetsBurst": 2      // Dataset list burst capacity
  },
  "ports": {
    "mainPort": 3000           // Default port for the server
  }
}

These settings can be deployed in various environments to ensure optimal performance and security.

❓ Frequently Asked Questions (FAQ)

1. Can Axiom MCP Server support multiple MCP clients simultaneously? Yes, Axiom MCP Server is designed to handle requests from multiple MCP clients concurrently. Proper configuration of rate limits ensures smooth operation with diverse clients.

2. How does the AXIOM_QUERY_RATE setting affect data retrieval in real-time use cases? The query rate limit controls the number of queries per second, which can impact performance in real-time scenarios like fraud detection analysis. Adjusting this value helps manage load and optimize response times.

3. What are dataset operations, and how do they differ from queries? Dataset operations include listing available datasets, which is separate from executing APL queries. They allow clients to discover accessible data sources without initiating complex query processes.

4. How does Axiom MCP Server ensure data security during transmission? All communications with the server are secured through HTTPS protocols, ensuring that sensitive API tokens and other credentials are transmitted securely between the client and the server.

5. Are there any specific tools required for running this MCP protocol implementation? Basic Node.js environment and npm or yarn package manager are sufficient to run Axiom MCP Server out of the box. No additional tools are needed, aside from the necessary environment configurations.

👨‍💻 Development & Contribution Guidelines

Contributors interested in enhancing or customizing Axiom MCP Server can follow these guidelines:

1. Fork the Repository: Start by forking the official repository on GitHub.
2. Clone Locally: Clone the forked repository to your local machine using git clone <fork-url>.
3. Contribute Code: Add new features, fix bugs, or improve documentation as needed. Ensure your contributions align with existing coding standards and best practices.
4. Run Tests: Before submitting a pull request, run tests using npm test to verify the integrity of your changes.

Pull requests are warmly welcomed, allowing the community to build and refine this essential AI integration tool.

🌐 MCP Ecosystem & Resources

Axiom MCP Server is part of a broader ecosystem that includes various tools, resources, and documentation. For more information on how to integrate Axiom MCP Server into your projects or for additional help, visit the official MCP Server GitHub Page or explore related resources in the MCP community.

By leveraging Axiom MCP Server, developers can seamlessly integrate complex data management functionalities into their AI applications, enhancing performance and reliability.