What is Plugin Comput3ai Mcp

plugin-comput3ai-mcp is a powerful integration plugin that connects ElizaOS with the Model Context Protocol (MCP), allowing AI agents to utilize multiple MCP servers for enhanced functionalities.

Use cases

Use cases include enhancing conversational AI agents, automating workflows with dynamic prompts, and leveraging contextual data for improved decision-making in AI applications.

How to use

To use plugin-comput3ai-mcp, create an account on https://comput3.ai/, top up your account, and launch GPUs. Clone the Eliza starter repository, configure the .env file with your MCP settings, and install the plugin in your ElizaOS project.

Key features

Key features include access to smart resources for contextual data, dynamic prompts for templated messages, and powerful tools for executing complex functions.

Where to use

plugin-comput3ai-mcp can be used in AI development environments, particularly in applications that require integration with multiple data sources and advanced AI capabilities.

Comput3AI MCP Plugin

A powerful integration plugin that bridges ElizaOS with the Model Context Protocol (MCP), enabling your AI agents to harness multiple MCP servers for enhanced capabilities.

🌟 Overview

The Model Context Protocol (MCP) is a revolutionary open protocol that creates a seamless bridge between Large Language Models (LLMs) and external resources. It standardizes how AI applications interact with external data and tools, making integration simple and efficient.

✨ Key Features

This plugin supercharges your ElizaOS agents by providing access to multiple MCP servers, each offering unique capabilities:

• Smart Resources: Access and utilize contextual data and information
• Dynamic Prompts: Leverage templated messages and workflows
• Powerful Tools: Execute sophisticated functions and operations

🚀 Getting Started

create an account on
https://comput3.ai/

top up your account and launch gpus

get your eliza agent on

git clone https://github.com/elizaos/eliza-starter.git
cd eliza-starter
cp .env.example .env
pnpm i && pnpm build && pnpm start

add compute3 configurations to the .env file.

OPENAI_API_KEY=c3_api_key
OPENAI_API_URL=https://api.comput3.ai/v1
SMALL_OPENAI_MODEL=hermes3:70b
MEDIUM_OPENAI_MODEL=hermes3:70b
LARGE_OPENAI_MODEL=hermes3:70b

To integrate this plugin into your ElizaOS project:

📦 Installation

Install the plugin in your ElizaOS project:

packages/
├─plugin-comput3ai-mcp/    # Your plugin directory
   ├── package.json
   ├── tsconfig.json
   ├── src/
   │   ├── index.ts        # Main plugin entry
   │   ├── actions/        # Custom actions
   │   ├── providers/      # Data providers
   │   ├── types.ts        # Type definitions
   │   └── environment.ts  # Configuration

1. Clone the repository:

cd packages
git clone github:comput3ai/plugin-comput3ai-mcp

• npm

npm install @compute3ai/plugin-compute3ai-mcp

• pnpm

pnpm install @compute3ai/plugin-compute3ai-mcp

• yarn

yarn add @compute3ai/plugin-compute3ai-mcp

• bun

bun add @compute3ai/plugin-compute3ai-mcp

🚀 Usage

1.deploy and mcp server

• examples can be found here https://github.com/modelcontextprotocol/servers/

• or you can use https://n8n.io/

2. Add the plugin to your character configuration:

⚙️ Configuration Options

MCP supports two types of servers: “stdio” and “sse”. Each type has its own configuration options.

Common Options

stdio Server Options

sse Server Options

🛠️ Using MCP Capabilities

Once configured, the plugin automatically exposes MCP servers’ capabilities to your agent:

Context Providers

The plugin includes three providers that add MCP capabilities to the agent’s context:

1. MCP_SERVERS: Lists available servers and their tools, resources and prompts

🔄 Plugin Flow

The following diagram illustrates the MCP plugin’s flow for tool selection and execution:

graph TD
    %% Starting point - User request
    start[User Request] --> action[CALL_TOOL Action]

    %% MCP Server Validation
    action --> check{MCP Servers Available?}
    check -->|No| fail[Return No Tools Available]
    
    %% Tool Selection Flow
    check -->|Yes| state[Get MCP Provider Data]
    state --> prompt[Create Tool Selection Prompt]
    
    %% First Model Use - Tool Selection
    prompt --> model1[Use Compute3ai for Tool Selection]
    model1 --> parse[Parse Selection]
    parse --> retry{Valid Selection?}
    
    %% Second Model Use - Retry Selection
    retry -->|No| feedback[Generate Feedback]
    feedback --> model2[Use Compute3ai for Retry]
    model2 --> parse
    
    %% Tool Selection Result
    retry -->|Yes| toolAvailable{Tool Available?}
    toolAvailable -->|No| fallback[Fallback Response]
    
    %% Tool Execution Flow
    toolAvailable -->|Yes| callTool[Call MCP Tool]
    callTool --> processResult[Process Tool Result]
    
    %% Memory Creation
    processResult --> createMemory[Create Memory Record]
    createMemory --> reasoningPrompt[Create Reasoning Prompt]
    
    %% Third Model Use - Response Generation
    reasoningPrompt --> model3[Use Compute3ai for Response]
    model3 --> respondToUser[Send Response to User]
    
    %% Styling
    classDef model fill:#ffa500,stroke:#333,stroke-width:2px;
    classDef decision fill:#bbf,stroke:#333,stroke-width:2px;
    classDef output fill:#bfb,stroke:#333,stroke-width:2px;
    
    class model1,model2,model3 model;
    class check,retry,toolAvailable decision;
    class respondToUser,fallback output;

📋 Example: Setting Up Multiple MCP Servers

Here’s a complete example configuration with multiple MCP servers of both types:

{
  "name": "Developer Assistant",
  "plugins": [
    "@elizaos/plugin-mcp",
    "other-plugins"
  ],
  "settings": {
    "mcp": {
      "servers": {
        "github": {
          "command": "npx",
          "args": [
            "-y",
            "@modelcontextprotocol/server-github"
          ],
          "env": {
            "GITHUB_PERSONAL_ACCESS_TOKEN": "<YOUR_TOKEN>"
          }
        },
        "puppeteer": {
          "command": "npx",
          "args": [
            "-y",
            "@modelcontextprotocol/server-puppeteer"
          ]
        },
        "google-maps": {
          "command": "npx",
          "args": [
            "-y",
            "@modelcontextprotocol/server-google-maps"
          ],
          "env": {
            "GOOGLE_MAPS_API_KEY": "<YOUR_API_KEY>"
          }
        }
      },
      "maxRetries": 2
    }
  }
}

🔒 Security Considerations

Please be aware that MCP servers can execute arbitrary code, so only connect to servers you trust.

🔍 Troubleshooting

If you encounter issues with the MCP plugin:

1. Check that your MCP servers are correctly configured and running
2. Ensure the commands are accessible in the ElizaOS environment
3. Review the logs for connection errors
4. Verify that the plugin is properly loaded in your character configuration