Get up and running with your first MCP server in just a few steps. This guide walks you through signing in, deploying an MCP server, and testing it in the playground.

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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.

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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.

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Step 3: Test in Playground

Once your MCP server is deployed: Go to the Playground section. Select your MCP server from the list. Choose an LLM model (e.g., GPT-4, GPT-4o, GPT-4o-mini, etc.). Send requests and view live responses from your MCP server. You can compare results across different models to evaluate behavior and performance.

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Step 4: View Logs and Analytics (Coming Soon)

Head to Observability > Logs & Analytics. Use filters to monitor real-time usage, performance, and errors. Our open-source client library lets you easily integrate logging into your MCP server code.

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Step 5: Set up Access Control (Coming Soon)

Head to Access Control > Teams & Policies. Define access policies at the team or individual level. Control visibility and usage of MCP servers and tools across departments or clients.

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You’re All Set!

You’ve now:

  • Signed in
  • Deployed your first MCP server
  • Tested it with real models
  • Viewed logs and metrics (Coming Soon)
  • (Optionally) Set up access control (Coming Soon)

Start building intelligent, composable tools with the power of Model Context Protocols and LLMs.