Used for running the server with commands like 'bun install', 'bun run build', and 'bun run dev'
Provides containerization and simplified deployment to EC2 or other server environments with included Docker configuration
Used for cloning the repository during deployment to EC2
Used for type-safe implementation of the MCP server, with build step to compile TypeScript code
Mentioned as a potential OS for EC2 deployment alongside Amazon Linux 2
LLM Responses MCP Server
A Model Context Protocol (MCP) server that allows multiple AI agents to share and read each other's responses to the same prompt.
Overview
This project implements an MCP server with two main tool calls:
submit-response: Allows an LLM to submit its response to a promptget-responses: Allows an LLM to retrieve all responses from other LLMs for a specific prompt
This enables a scenario where multiple AI agents can be asked the same question by a user, and then using these tools, the agents can read and reflect on what other LLMs said to the same question.
Related MCP server: Model Context Provider (MCP) Server
Installation
Development
Testing with MCP Inspector
The project includes support for the MCP Inspector, which is a tool for testing and debugging MCP servers.
The inspect script uses npx to run the MCP Inspector, which will launch a web interface in your browser for interacting with your MCP server.
This will allow you to:
Explore available tools and resources
Test tool calls with different parameters
View the server's responses
Debug your MCP server implementation
Usage
The server exposes two endpoints:
/sse- Server-Sent Events endpoint for MCP clients to connect/messages- HTTP endpoint for MCP clients to send messages
MCP Tools
submit-response
Submit an LLM's response to a prompt:
get-responses
Retrieve all LLM responses, optionally filtered by prompt:
License
MIT
Deployment to EC2
This project includes Docker configuration for easy deployment to EC2 or any other server environment.
Prerequisites
An EC2 instance running Amazon Linux 2 or Ubuntu
Security group configured to allow inbound traffic on port 62886
SSH access to the instance
Deployment Steps
Clone the repository to your EC2 instance:
git clone <your-repository-url> cd <repository-directory>Make the deployment script executable:
chmod +x deploy.shRun the deployment script:
./deploy.sh
The script will:
Install Docker and Docker Compose if they're not already installed
Build the Docker image
Start the container in detached mode
Display the public URL where your MCP server is accessible
Manual Deployment
If you prefer to deploy manually:
Build the Docker image:
docker-compose buildStart the container:
docker-compose up -dVerify the container is running:
docker-compose ps
Accessing the Server
Once deployed, your MCP server will be accessible at:
http://<ec2-public-ip>:62886/sse- SSE endpointhttp://<ec2-public-ip>:62886/messages- Messages endpoint
Make sure port 62886 is open in your EC2 security group!