OpenAPI Schema Explorer MCP Server

What does “OpenAPI Schema Explorer” MCP Server do?

The OpenAPI Schema Explorer MCP Server provides token-efficient access to OpenAPI/Swagger specifications through MCP Resources, enabling client-side exploration of API schemas. This server acts as a bridge between AI assistants and external API documentation, allowing tools and LLMs (Large Language Models) to programmatically query, read, and analyze API specifications. By exposing OpenAPI/Swagger specs as structured resources, it streamlines tasks such as endpoint discovery, parameter inspection, and schema validation, enhancing the development workflow for teams integrating or building upon third-party APIs. This server is particularly useful for developers and AI agents looking to automate API documentation analysis, improve code generation, or validate integration points in a scalable and standardized manner.

List of Prompts

No explicit prompt templates are mentioned in the available repository files or documentation.

List of Resources

• OpenAPI/Swagger Specifications
  Exposes OpenAPI and Swagger specification documents as structured MCP Resources for efficient retrieval and exploration.
• API Endpoints
  Provides a resource view of all available endpoints within a given OpenAPI/Swagger spec for easy listing and selection.
• Schema Definitions
  Enables access to schema definitions and components within the API spec, supporting validation and type-checking tasks.

List of Tools

No explicit tools are listed in server.py or equivalent entrypoint files in the repository.

Use Cases of this MCP Server

• API Documentation Exploration
  Allows AI assistants and developers to programmatically explore and navigate OpenAPI/Swagger documentation, improving onboarding and automation.
• Endpoint Discovery
  Enables quick identification and listing of available endpoints in a target API, supporting rapid prototyping and integration.
• Schema Validation
  Facilitates automated validation of request and response schemas, ensuring compatibility and reducing integration errors.
• Code Generation Support
  Provides structured access to spec details, aiding tools that auto-generate client code or stubs from OpenAPI definitions.
• Automated Testing Setup
  Assists in extracting test cases or mock data by exposing schemas and parameters required for constructing API requests.

How to set it up

Windsurf

1. Ensure prerequisites are installed (e.g., Node.js, Docker if required).
2. Locate the Windsurf configuration file (typically windsurf.config.json).
3. Add the OpenAPI Schema Explorer MCP Server using the following JSON snippet:

   {
     "mcpServers": {
       "openapi-schema-explorer": {
         "command": "npx",
         "args": ["@kadykov/mcp-openapi-schema-explorer@latest"]
       }
     }
   }
   

4. Save your configuration and restart Windsurf.
5. Verify that the server is running and accessible from your client.

Securing API Keys:

{
  "mcpServers": {
    "openapi-schema-explorer": {
      "env": {
        "API_KEY": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
      },
      "inputs": {
        "api_key": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
      }
    }
  }
}

Claude

1. Install necessary dependencies (Node.js, etc.).
2. Edit the Claude platform’s MCP configuration file.
3. Insert the following JSON under the mcpServers section:

   {
     "mcpServers": {
       "openapi-schema-explorer": {
         "command": "npx",
         "args": ["@kadykov/mcp-openapi-schema-explorer@latest"]
       }
     }
   }
   

4. Save configuration and restart Claude.
5. Confirm the MCP server is listed in the available integrations.

Securing API Keys:

{
  "env": {
    "API_KEY": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  },
  "inputs": {
    "api_key": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  }
}

Cursor

1. Verify Node.js and other prerequisites are installed.
2. Open the Cursor platform’s settings or config file.
3. Add the MCP server using:

   {
     "mcpServers": {
       "openapi-schema-explorer": {
         "command": "npx",
         "args": ["@kadykov/mcp-openapi-schema-explorer@latest"]
       }
     }
   }
   

4. Save and reload Cursor.
5. Check the integration by listing available servers.

Securing API Keys:

{
  "env": {
    "API_KEY": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  },
  "inputs": {
    "api_key": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  }
}

Cline

1. Ensure all prerequisites (Node.js, etc.) are installed.
2. Find and open the Cline configuration file.
3. Insert this JSON to enable the server:

   {
     "mcpServers": {
       "openapi-schema-explorer": {
         "command": "npx",
         "args": ["@kadykov/mcp-openapi-schema-explorer@latest"]
       }
     }
   }
   

4. Save the file and restart Cline.
5. Verify the MCP server appears in your environment.

Securing API Keys:

{
  "env": {
    "API_KEY": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  },
  "inputs": {
    "api_key": "${OPENAPI_SCHEMA_EXPLORER_API_KEY}"
  }
}

How to use this MCP inside flows

Using MCP in FlowHunt

To integrate MCP servers into your FlowHunt workflow, start by adding the MCP component to your flow and connecting it to your AI agent:

Click on the MCP component to open the configuration panel. In the system MCP configuration section, insert your MCP server details using this JSON format:

{
  "openapi-schema-explorer": {
    "transport": "streamable_http",
    "url": "https://yourmcpserver.example/pathtothemcp/url"
  }
}

Once configured, the AI agent is now able to use this MCP as a tool with access to all its functions and capabilities. Remember to change “openapi-schema-explorer” to whatever the actual name of your MCP server is and replace the URL with your own MCP server URL.

Overview

Based on the above, OpenAPI Schema Explorer MCP provides useful documentation and setup, but lacks explicit prompt and tool definitions, which limits its out-of-the-box agentic versatility. It’s a solid resource-focused MCP, but may need further development or documentation for advanced use.
Rating: 6/10

MCP Score