Integrations
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.
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:Copy
- Make the deployment script executable:Copy
- Run the deployment script:Copy
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:Copy
- Start the container:Copy
- Verify the container is running:Copy
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!
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Enables multiple AI agents to share and read each other's responses to the same prompt, allowing them to reflect on what other LLMs said to the same question.
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