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@nl-framework/mcp-server

v0.3.5

Published

Model Context Protocol server for the Nael Framework. Provides interactive documentation, scaffolding prompts, and project bootstrap helpers for AI assistants.

Readme

Nael MCP Server

The Nael MCP Server packages up the Nael Framework documentation, tooling examples, and guided prompts behind the Model Context Protocol so that AI assistants can integrate directly with the platform. It supports multiple transports (stdio, Server-Sent Events, and a streamable HTTP API) and is published as @nl-framework/mcp-server on npm.

Latest builds now ship with the scheduler package documentation and examples, so MCP clients can explore cron/interval decorators, worker-backed execution, and the new examples/scheduler project without leaving their agent environment.

Local development

bun install
bun run --cwd packages/mcp-server dev:sse

This launches the SSE transport on http://localhost:3000 by default. Use dev for stdio mode or dev:http for the experimental streamable transport.

Docker

A Bun-based Dockerfile lives alongside the package and performs a full install, build, and production prune in two stages. The resulting image ships only the compiled dist/ output plus production dependencies and defaults to the SSE transport.

Build the image:

bun run --cwd packages/mcp-server docker:build

Run the container:

bun run --cwd packages/mcp-server docker:run

The container exposes port 3000; override the port or transport at runtime with environment variables:

docker run --rm -e PORT=4000 -p 4000:4000 nl-framework/mcp-server

To switch transports, override the command:

docker run --rm -p 3000:3000 nl-framework/mcp-server bun dist/index.js

Deployment notes

  • The Dockerfile uses oven/bun:latest for both build and runtime stages, keeping everything on the latest Bun release.
  • The build stage installs dependencies across the whole monorepo to compile TypeScript, then re-installs production dependencies scoped to @nl-framework/mcp-server.
  • The runtime stage copies only the compiled output and the trimmed node_modules, yielding a compact image that is ready to deploy to any container runtime.