Getting Started | MCPLambda Docs

Get from zero to a live MCP endpoint in a few minutes. Pick the path that fits how you work — dashboard UI or the mcpl CLI — then connect your AI client.

Visit mcplambda.io and sign in with GitHub or Google. That creates your account and first project.

Path A: Dashboard

Click Create Deployment.
Choose a Deployment Flow — Package, Git, or Image — or open Registry in the sidebar, find a server, and install it (pre-fills the form).
Example package source: npx://@mcp/server-time.
Name the deployment (e.g. time-server).
Click Deploy.

Within seconds you should see live status and logs. When the status is running, copy the Deployment URL.

Path B: mcpl CLI

Install

macOS / Linux:

curl -fsSL https://mcplambda.io/mcpl/install.sh | sh

Windows (PowerShell 5.1+):

irm https://mcplambda.io/mcpl/install.ps1 | iex

mcpl login
mcpl deploy npx://@mcp/server-time

mcpl login opens the browser for GitHub or Google. Tokens are stored in ~/.mcpl/config.json. The deploy command streams build logs and prints the deployment URL when the server is running.

Optional: discover a server first, then deploy the package or image it lists:

mcpl registry search time
mcpl registry info <name>
mcpl deploy npx://@mcp/server-time

Full command reference: The mcpl CLI.

Registry as an alternative install path

Prefer browsing over typing package names? Use the MCP Server Registry:

Dashboard: Sidebar → Registry → search / filter → install into your project.
CLI: mcpl registry search / mcpl registry info.
API: public GET /v1/registry/servers (no auth for reads).
AI client: search_registry via the MCPLambda MCP server.

Bring-your-own package, Git repo, or Docker image remains fully supported — the registry is convenience discovery, not a requirement.

2. Connect Your AI Client

Use the Deployment URL from the dashboard or CLI output.

Cursor / VS Code extensions: paste the URL in MCP settings (Streamable HTTP or SSE, depending on transport).
Claude Desktop and other local clients: use the URL (and API key if you chose auth_type: key; default oauth is handled by the client).

Step-by-step client configs: Connecting AI Clients.

3. What to do next

Once traffic hits the server, open the deployment → Analytics tab for tool call volume, error rates, and latency (Tool-Usage Analytics).