Auth proxy for Model Context Protocol servers. Adds authentication to MCP tools like Claude.ai, Claude Code, Cursor, and Gemini. Benefits operations teams by securing access to AI agents and workflows. Integrates with existing MCP infrastructure.
git clone https://github.com/stainless-api/mcp-front.gitAuth proxy for Model Context Protocol servers. Adds authentication to MCP tools like Claude.ai, Claude Code, Cursor, and Gemini. Benefits operations teams by securing access to AI agents and workflows. Integrates with existing MCP infrastructure.
["Install and configure the MCP Front proxy on your server using the official documentation. Ensure your MCP server is running and accessible at the specified address.","Choose an authentication method (API key, OAuth, or JWT) and generate the required credentials. For JWT, use a tool like `jwt.io` to create a token with the appropriate claims.","Update the proxy configuration file (e.g., `mcp-front-config.json`) with the server details, authentication settings, and rate limits. Example:\n```json\n{\n \"server_name\": \"my-mcp-server\",\n \"server_address\": \"localhost:8080\",\n \"auth_method\": \"JWT\",\n \"credentials\": \"your_jwt_token_here\",\n \"target_endpoint\": \"http://localhost:3000/mcp\",\n \"rate_limit\": 100\n}\n```","Start the proxy service and verify it is running. Use a tool like `curl` or Postman to send a test request to the proxy endpoint, including the required authentication headers.","Monitor the proxy logs for any errors or unauthorized access attempts. Adjust rate limits or authentication settings as needed based on usage patterns."]
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/stainless-api/mcp-frontCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Configure the MCP Front proxy to secure access to [MCP_SERVER_NAME] running on [SERVER_ADDRESS:PORT]. Set up [AUTH_METHOD] authentication (e.g., API key, OAuth, JWT) with [CREDENTIALS]. Ensure the proxy routes requests to [TARGET_ENDPOINT] while enforcing rate limits of [RATE_LIMIT] requests per minute. Test the setup by sending a sample request to [TEST_ENDPOINT].
```json
{
"status": "success",
"proxy_config": {
"server_name": "code-analysis-mcp",
"server_address": "localhost:8080",
"auth_method": "JWT",
"credentials": "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
"target_endpoint": "http://localhost:3000/mcp",
"rate_limit": "100",
"test_results": {
"request_sent": {
"endpoint": "/analyze-code",
"method": "POST",
"headers": {
"Authorization": "Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...",
"Content-Type": "application/json"
},
"body": {
"language": "python",
"code": "def hello(): return 'world'"
}
},
"response": {
"status_code": 200,
"body": {
"analysis": "Code is syntactically correct and follows PEP 8 guidelines.",
"suggestions": ["Consider adding docstrings."]
}
}
}
}
}
```
The MCP Front proxy is now successfully configured to secure access to the code analysis MCP server. The JWT authentication is enforced, and the proxy correctly routes requests to the target endpoint while maintaining the rate limit. The test request to `/analyze-code` was processed without errors, returning a valid analysis of the provided Python code. The response includes actionable feedback, demonstrating that the proxy is functioning as expected. Operations teams can now securely expose this MCP server to authorized clients like Claude Code or Cursor without exposing the underlying server directly.Google's multimodal AI model and assistant
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