Step 1: Sign In or Create an Account
Go to platform.contexaai.com and sign in using your credentials. Don’t have an account? Click Sign Up to register in seconds.Step 2: Deploy Your MCP Server
Choose one of the following ways to deploy: 🔍 Option 1: Use a Curated Server Navigate to the MCP Directory. Browse verified servers contributed by the verified developers and organizations. Click Deploy on any server to set it up instantly. 🔗 Option 2: Bring Your Own Server Go to Directory > Add Server > via GitHub. Deploy via Github Enter public GitHub repo URL containing your MCP code. Configure deployment settings and click Deploy. 📄 Option 3: Create from OpenAPI Spec Navigate to Directory > Add Server > via OpenAPI. Deploy via OpenAPI Upload your OpenAPI 3.0 spec file or paste the spec in the editor. Name your server and click Deploy.Step 3: Test in the Playground
Once your MCP server is deployed:- Go to the Playground section.
- Select your MCP server from the dropdown list.
- Choose an LLM model (e.g., GPT-4, GPT-4o, GPT-4o-mini).
- Send a request and see live responses from your MCP server.
- Optionally, compare outputs across different models to evaluate performance.
Step 4: View Traces & Logs
- Navigate to Traces.
- Platform Logs: See all tool calls with timestamps, inputs, outputs, and status.
- Server Session Logs: View grouped logs by session for detailed analysis.
- Use filters to drill down into specific tools or calls.
✅ You’re All Set!
You’ve now:- ✅ Signed in
- ✅ Deployed your first MCP server
- ✅ Tested it with real models
- ✅ Viewed logs and metrics