octo-mcp-server
A production-ready MCP server built with Node.js and Express that supports remote deployment via HTTP and SSE. It provides a modular framework for building and scaling tools while serving multiple clients concurrently.
README
octo-mcp-server
A production-ready Model Context Protocol (MCP) server built with Node.js, TypeScript, and Express. It uses HTTP + SSE (Server-Sent Events) as the transport so it can be deployed remotely and serve multiple clients concurrently.
Project structure
src/
index.ts # Entry point — creates Express app, mounts /sse and /message routes
server.ts # MCP server factory, session registry, message routing
tools/
echo.ts # Example tool: returns its input unchanged
Dockerfile
tsconfig.json
package.json
.env.example
Adding a new tool
- Create
src/tools/my-tool.tsand export aregisterMyTool(server: McpServer)function:
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import * as z from 'zod/v4';
export function registerMyTool(server: McpServer): void {
server.tool(
'my-tool',
'Description shown to the LLM',
{ input: z.string() },
async ({ input }) => ({
content: [{ type: 'text', text: `Result: ${input}` }],
}),
);
}
- Import and call it in
src/server.ts:
import { registerMyTool } from './tools/my-tool.js';
// inside createMcpServer:
registerMyTool(server);
That's it.
Local development
Prerequisites
- Node.js ≥ 18
- npm
Setup
cp .env.example .env # edit PORT or add API keys as needed
npm install
npm run build
npm start
The server starts on http://localhost:3000 (or whatever PORT is set to).
Verify with curl
# Health check
curl http://localhost:3000/health
# Open an SSE stream (keep this terminal open)
curl -N http://localhost:3000/sse
# You will see: event: endpoint\ndata: /message?sessionId=<ID>
# In another terminal, call the echo tool (replace <SESSION_ID>)
curl -X POST "http://localhost:3000/message?sessionId=<SESSION_ID>" \
-H "Content-Type: application/json" \
-d '{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "echo",
"arguments": { "message": "hello world" }
}
}'
Available npm scripts
| Script | Description |
|---|---|
npm run build |
Compile TypeScript → dist/ |
npm start |
Run the compiled server |
npm run dev |
Run with ts-node (no compile) |
npm run clean |
Delete dist/ |
Docker
# Build
docker build -t octo-mcp-server .
# Run (pass environment variables with -e or --env-file)
docker run -p 3000:3000 --env-file .env octo-mcp-server
Deploy to Azure Web App
Option A — Deploy a Docker container (recommended)
- Push your image to a container registry (Azure Container Registry, Docker Hub, etc.):
az acr build --registry <your-registry> --image octo-mcp-server:latest .
- Create the Web App (Linux, Docker):
az group create --name rg-octo-mcp --location eastus
az appservice plan create \
--name plan-octo-mcp \
--resource-group rg-octo-mcp \
--is-linux \
--sku B1
az webapp create \
--name octo-mcp-server \
--resource-group rg-octo-mcp \
--plan plan-octo-mcp \
--deployment-container-image-name <your-registry>.azurecr.io/octo-mcp-server:latest
- Set environment variables:
az webapp config appsettings set \
--name octo-mcp-server \
--resource-group rg-octo-mcp \
--settings PORT=3000 MY_API_KEY=...
- Enable Always On so the server stays warm:
az webapp config set \
--name octo-mcp-server \
--resource-group rg-octo-mcp \
--always-on true
SSE note: Azure App Service by default has a 230-second idle request timeout. For long-lived SSE connections you may need to send keep-alive comments or configure the timeout via
az webapp config set --http20-enabled true.
Option B — Deploy from source with Oryx build
- Zip the source (exclude
node_modulesanddist):
zip -r deploy.zip . --exclude "node_modules/*" "dist/*" ".git/*"
- Deploy:
az webapp deployment source config-zip \
--name octo-mcp-server \
--resource-group rg-octo-mcp \
--src deploy.zip
Azure will run npm install && npm run build && npm start automatically via the Oryx build system.
Environment variables
| Variable | Default | Description |
|---|---|---|
PORT |
3000 |
TCP port the server listens on |
Add any tool-specific secrets (API keys, connection strings) here as well.
API endpoints
| Method | Path | Description |
|---|---|---|
| GET | /health |
Returns {"status":"ok","timestamp":"…"} |
| GET | /sse |
Opens an SSE stream; emits the POST endpoint + session ID |
| POST | /message |
Receives JSON-RPC 2.0 messages (?sessionId=<id>) |
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.