mcp4gql - GraphQL MCP Server

Overview: What is mcp4gql MCP Server?

mcp4gql is a Node.js/TypeScript server that implements the Model Context Protocol (MCP). It serves as an essential bridge, enabling MCP clients like Cursor and Continue to interact with target GraphQL APIs. By adhering to the MCP protocol, this server facilitates seamless integration of diverse AI applications with various data sources or tools, thereby enhancing their functionality and utility.

🔧 Core Features & MCP Capabilities

mcp4gql offers a range of features that make it an indispensable tool for developers integrating AI applications with GraphQL APIs. It primarily focuses on implementing the Server class from @modelcontextprotocol/sdk, providing robust support for standards-compliant MCP interactions. Specifically, mcp4gql supports communication via standard input/output and uses axios to send requests to configured GraphQL endpoints.

For developers working with specific tools or queries, mcp4gql exposes generic GraphQL tools such as introspectGraphQLSchema and executeGraphQLOperation. These tools enable clients to introspect the schema of a target GraphQL API and execute arbitrary queries or mutations against it. This capability significantly simplifies the process for integrating MCP clients with various backend systems.

Diagram: Core Features

graph TB
    A["Implement `Server` from @modelcontextprotocol/sdk"]
    B["Standard Input/Output Communication (Stdio)"]
    C["GraphQL API Requests via axios"]
    D[Expose GraphQL Tools]
    E[Tools: `introspectGraphQLSchema` & `executeGraphQLOperation`]

    A --> B
    A --> C
    C --> D
    D --> E

    style A fill:#e1f5fe
    style B fill:#f3e5f5
    style C fill:#f5e8f5
    style D fill:#e8f5ee
    style E fill:#e9fedd

⚙️ MCP Architecture & Protocol Implementation

Internally, mcp4gql follows a well-designed architecture that ensures seamless and efficient protocol handling. It leverages the open-source @modelcontextprotocol/sdk to implement its core functionality, ensuring compatibility with other MCP clients. The server's primary component is the Server class from @modelcontextprotocol/sdk, which handles communication between the client and the target GraphQL API.

Diagram: Protocol Flow

graph TD
    A["AI Application"] --> B[MCP Client]
    B --> C[mcp4gql Server]
    C --> D[GraphQL Endpoint]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Diagram: Data Architecture

graph TD
    A["MCP Client"] --> B[mcp4gql Server]
    B --> C[GraphQL API]
    style A fill:#e1f5fe
    style B fill:#f3e5f5
    style C fill:#e8f5e8

🚀 Getting Started with Installation

To get started, developers need to ensure that the required software and dependencies are installed on their machines. The following steps outline the installation process for mcp4gql:

1. Install Node.js: Ensure you have Node.js installed on your machine.
2. Clone the Repository: Clone this repository using Git.
3. Install Dependencies: Run npm install to install all required dependencies.
4. Configure Environment Variables:
   • Set the GRAPHQL_ENDPOINT environment variable with the URL of the target GraphQL API.
   • Optionally, set the AUTH_TOKEN for authentication purposes.

💡 Key Use Cases in AI Workflows

mcp4gql serves as a critical component in various AI workflows by facilitating interactions between AI applications and backend systems. Here are two realistic use cases:

1. Data Retrieval and Analysis:

   • Scenario: A financial analyst uses Cursor to interact with GraphQL APIs that provide market data.
   • Implementation: By using mcp4gql, the analyst can query relevant market information directly from the backend API.
   • Technical Details: The executeGraphQLOperation tool is used to fetch and process complex queries, ensuring timely and accurate data retrieval.

2. Model Training and Validation:

   • Scenario: A machine learning engineer needs to train a model using historical sales data.
   • Implementation: mcp4gql enables the integration of Cursor with the backend GraphQL API hosting the sales data.
   • Technical Details: The introspectGraphQLSchema tool is used to understand the schema, and executeGraphQLOperation is utilized for retrieving data needed for model training.

🔌 Integration with MCP Clients

Integrating mcp4gql with MCP clients like Cursor or Continue involves configuring these applications appropriately. Developers need to add the following configuration details in their respective settings:

Cursor Configuration

1. Go to Cursor MCP Settings:
   • Open Cursor and navigate to Settings > Cursor Settings > MCP.
2. Add New Global MCP Server:
   • Click on + Add new global MCP server.
3. Configure mcp4gql:

   {
     "mcpServers": {
       "mcp4gql": {
         "command": "npx",
         "type": "stdio",
         "args": ["-y", "mcp4gql"],
         "env": {
           "GRAPHQL_ENDPOINT": "YOUR_GRAPHQL_ENDPOINT_URL",
           "AUTH_TOKEN": "YOUR_OPTIONAL_AUTH_TOKEN"
         }
       }
     }
   }
   

Claude Desktop Configuration

1. Open Claude Desktop Settings:
   • Launch Claude Desktop and go to Developer > Edit Config.
2. Add mcp4gql Configuration:

   {
     "mcpServers": {
       "mcp4gql": {
         "command": "npx",
         "args": ["-y", "mcp4gql"],
         "env": {
           "GRAPHQL_ENDPOINT": "YOUR_GRAPHQL_ENDPOINT_URL",
           "AUTH_TOKEN": "YOUR_OPTIONAL_AUTH_TOKEN"
         }
       }
     }
   }
   

Once these configurations are in place, MCP clients should be able to utilize the introspectGraphQLSchema and executeGraphQLOperation tools seamlessly.

📊 Performance & Compatibility Matrix

mcp4gql is built with cross-client compatibility in mind. The following table summarizes its compatibility matrix with popular MCP clients:

MCP Client	Resources	Tools (introspectGraphQLSchema, executeGraphQLOperation)	Prompts (custom prompts for interaction)	Status
Cursor	✅	✅	❌	Full Support
Continue	✅	✅	❌	Full Support
Claude Desktop	✅	✅	❌	Full Support

🛠️ Advanced Configuration & Security

For advanced integration scenarios, developers can customize various aspects of mcp4gql. Key areas include:

Environmental Variables

• GRAPHQL_ENDPOINT: The URL of the target GraphQL API.
• AUTH_TOKEN: A bearer token for optional authentication.

Customizing Tool Implementation

Developers can extend the server's behavior by modifying the implementation details of introspectGraphQLSchema and executeGraphQLOperation.

❓ Frequently Asked Questions (FAQ)

1. How do I troubleshoot issues with mcp4gql?

   • Check if all environment variables are correctly set, especially GRAPHQL_ENDPOINT.
   • Verify that the GraphQL API is accessible and properly configured.

2. Can I use multiple MCP servers in a single application setup?

   • Yes, you can set up additional MCP servers by adding more entries to your configuration file.

3. What if the target GraphQL API requires custom headers or paths?

   • Customize the axios requests within the server implementation as needed.

4. Are there any security best practices for using mcp4gql in production environments?

   • Ensure that all environment variables are secured and not exposed publicly.
   • Implement logging to monitor server activities for potential security breaches.

5. How can I improve performance of GraphQL queries executed via mcp4gql?

   • Optimize the GraphQL API schema to reduce complexity, which in turn improves query execution time.
   • Implement caching mechanisms at both client and server levels to minimize repeated requests.

👨‍💻 Development & Contribution Guidelines

If you wish to contribute to the development of mcp4gql, please follow these guidelines:

1. Fork the Repository: Fork this repository on GitHub.
2. Create a Branch: Create a new branch for your feature or bug fix.
3. Write Tests: Ensure that any new functionality is accompanied by adequate tests.
4. Commit Changes: Commit changes with clear and concise messages.
5. Pull Request: Open a pull request detailing the changes made.

🌐 MCP Ecosystem & Resources

For more information about Model Context Protocol (MCP), its clients, and related resources, please refer to the official MCP documentation and community forums.

By leveraging mcp4gql, developers can significantly enhance their AI application’s capabilities by integrating with diverse data sources and tools. This comprehensive guide aims to provide everything you need to get started and integrate mcp4gql into your projects efficiently.