-
securityA
license-
qualityA Model Context Protocol server that allows LLMs to interact with web content through standardized tools, currently supporting web scraping functionality.
Last updated -
1
MIT License
Used for configuration management through environment variables in both hub and server components
Serves as the foundation for the MCP hub, handling JSON-RPC requests at the /mcp endpoint and health checks at /health
Provides tool examples that can interact with GitHub through an API key configuration option
Serves as the runtime environment for the MCP server, with specific version requirements (v16 or higher)
Integrates with OpenAI services through an API key configuration, enabling AI capabilities for the MCP server
Used as the implementation language for the hub component, with TypeScript source files compiled to JavaScript
Used for bridge and tool definitions through YAML files in the bridges directory
MCP Burst
An Express app with AI capabilities powered by MCP (Model Context Protocol)
MCP Burst supports multiple server types and includes a built-in chat interface for testing. In a way acting as a bridge for MCP Clients to an array of tools and MCP servers/server gateways.
What it does
Chat Integration: Works with Ollama, OpenAI, and Docker Model Runner
MCP Server Support: Runs streamablehttp servers, stdio servers such as Docker MCP Gateway server, and n8n MCP trigger node URLs
Custom Tools: Create discoverable tools at the
/mcpendpointMulti-Client Support: Use
MCP_BURST_CLIENT=truein .env to serve multiple clients simultaneously
Quick Status Check
Session debugging:
curl http://localhost:4000/statusNote: Multi-client sessions are still being thoroughly tested
NOTE: You might have to upgrade the security if you want to use this in production. Otherwise, test and be patient until a secure merge
Running MCP Burst in MCP Clients
VSCode:
In your MCP Burst folder, run the hub:
npm run start:hub
Create .vscode/mcp.json in your workspces for example, using this config:
{
"servers": {
"mcp-burst": {
"type": "http",
"url": "http://127.0.0.1:4000",
}
}
}
Claude Desktop: Update your claude_desktop_config.json to include:
{
"mcpServers": {
"mcp-burst": {
"command": "node",
"args": ["/path/to/mcpburst/hub/stdio-client-hub-entry.js"]
}
}
}
Prebuilt Demo Chatbot Agent App
In your MCP Burst folder, run these commands: 1.
npm run start:hub
npm run start:server
Table of Contents
Features
Streamable HTTP MCP transport server built on Model Context Protocol SDK
Serve MCP Burst as an http and/or stdio client (tested with Claude Desktop, VS Code)
Built-in demo tools: 'echo' and 'update_session_planner'
Express façade handling JSON-RPC at
/mcpand health checks at/healthBuilt in Planner Tool (Required for built in chatbot, but not necessarily for MCP Clients.)
OPTIONAL: Built in Gamification (ie positive reinforcement for successfully completing tasks, worked well with Claude Desktop so I kept it in the repo)
Demo Chatbot Agent App to test MCP integration, and now session planner resource to execute multiple tools.
Prerequisites
Node.js v16 or higher
npm (included with Node.js)
Installation
Clone the repository:
git clone https://github.com/arberrexhepi/mcpburst.git cd mcpburstInstall root dependencies in root:
npm installInstall hub and server dependencies:
cd hub && npm install && cd ..
Configuration
Create environment variable files in both hub/ and server/ directories:
hub/.env
PORT=4000
HOST=localhost
MCP_REQUIRE_AUTH=false # set to 'true' to require Bearer auth NOTE:
MCP_BURST_CLIENT=true #set to false if you don't want it to be discoverable
server/.env
OPENAI_API_KEY=your_openai_api_key
MCP_ENDPOINT=http://127.0.0.1:4000/mcp
PORT = 3500
STRATEGY=DMR
DOCKER_MODEL_RUNNER_URL=http://localhost:12434/engines/llama.cpp/v1/chat/completions
OLLAMA_URL=http://localhost:11434/v1/chat/completions
Usage
Build and start the MCP hub server:
npm run start:hubStart the front-end proxy server:
npm run start:serverOpen your browser at http://localhost:3000 to access the chat UI.
The hub JSON-RPC endpoint is available at
http://localhost:4000/mcp.
Directory Structure
├── LICENSE
├── package.json # root package config and scripts
├── README.md
├── hub/ # MCP hub server
│ ├── package.json
│ ├── tsconfig.json
│ ├── dist/ # TypeScript sources output to dist/
│ ├── installToolsFeature.ts
│ ├── installResourcesFeature.ts
│ ├── stdio-client-hub-entry.js
│ ├── bridgeBuilder.ts
│ ├── bridgeHttp.ts
│ ├── bridgeStdio.ts
│ ├── hub.ts
│ └── bridges/ # sample tool definitions
│ └── hub.yaml
└── server/ # proxy and front-end assets
├── index.js
├── extractContent.js
├── public/
│ ├── index.html
│ ├── css/
│ │ └── styles.css
│ └── js/
│ └── chat.js
└── agent_functions/
├── index.js
├── llmClient.js
├── mcpClient.js
├── planExecutor.js
└── README.MD
Scripts
All scripts are defined in the root package.json:
npm run build: Compile TypeScript inhuband copy bridge filesnpm run copy:bridges: Copy bridge YAML definitions tohub/distnpm run start:hub: Build then run the MCP hub servernpm run start:server: Run the Express static server with chat UI
License
This project is licensed under the Apache License 2.0. See the LICENSE file for details.
This server cannot be installed
hybrid server
The server is able to function both locally and remotely, depending on the configuration or use case.
An Express server implementation of Model Context Protocol that allows websites to connect to LLMs through streamable HTTP and stdio transports, with a built-in chat UI for testing responses.
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