Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@sentiment-analyzer echo 'I am feeling great today!'"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP server created with MCPize.
npm install
npm run dev # Start with hot reloadServer runs at http://localhost:8080/mcp
Related MCP server: mcpv3e
npm run dev # Development mode with hot reload
npm run build # Compile TypeScript
npm test # Run tests
npm start # Run compiled server├── src/
│ ├── index.ts # MCP server entry point
│ └── tools.ts # Pure tool functions (testable)
├── tests/
│ └── tools.test.ts # Tool unit tests
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript configuration
├── mcpize.yaml # MCPize deployment manifest
├── Dockerfile # Container build
└── .env.example # Environment variables templatehello — Returns a greeting message
echo — Echoes back the input with a timestamp
npm test # Run unit tests
npx @anthropic-ai/mcp-inspector # Interactive MCP testingConnect to http://localhost:8080/mcp to test tools interactively.
mcpize deployMIT
This server cannot be installed
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
List, configure, chat with, analyse and embed your Echo AI assistants.
httpbin echo: GET/POST inspection, status codes, delay, UUID, base64. Debug aid.
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We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/DON-VXNKS/mcp-sentiment-analyzer'
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