Get Started with EDDI

Prerequisites

• Docker (recommended) or Java 25+. On x86-64 hosts the EDDI image needs an x86-64-v3 CPU (Intel Haswell, AMD Excavator, or newer)
• An LLM provider API key (OpenAI, Anthropic, Google Gemini, or a local Ollama instance)

1. Install & Start EDDI

The fastest way to get EDDI running is the one-command installer. It sets up EDDI + your choice of database via Docker Compose, generates a vault encryption key, and walks you through configuration:

curl -fsSL https://raw.githubusercontent.com/labsai/EDDI/main/install.sh | bash

Invoke-WebRequest -Uri "https://raw.githubusercontent.com/labsai/EDDI/main/install.ps1" -OutFile "install.ps1"
Unblock-File .\install.ps1
.\install.ps1

git clone https://github.com/labsai/EDDI.git
cd EDDI
docker compose up

docker compose -f docker-compose.yml -f docker-compose.ollama.yml up -d

EDDI will be available at http://localhost:7070.

2. Connect via MCP

Connect your AI assistant to EDDI's 84 MCP tools. Configuration depends on your client's transport support:

{
  "mcpServers": {
    "eddi": {
      "url": "http://localhost:7070/mcp"
    }
  }
}

{
  "mcpServers": {
    "eddi": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "http://localhost:7070/mcp"]
    }
  }
}

Now you can interact with EDDI's 84 MCP tools directly from your AI assistant.

📖 See the MCP Server documentation for the complete tool reference and advanced configuration.

3. Store Your API Key

Before creating an agent, securely store your LLM provider API key in EDDI's Secrets Vault (AES-256-GCM encrypted):

curl -X PUT http://localhost:7070/secretstore/secrets/default/my-anthropic-key \
  -H "Content-Type: application/json" \
  -d '{"value": "sk-ant-your-actual-key", "description": "Anthropic API key"}'

💡 Tip: The ${vault:my-anthropic-key} syntax references EDDI's built-in Secrets Vault. The vault master key is auto-generated by the installer. For quick testing, you can also pass API keys directly: apiKey: "sk-ant-...".

4. Create Your First Agent

Use setup_agent to create a fully working agent in one call, via MCP or REST API:

setup_agent(
  agentName: "My first agent",
  systemPrompt: "You are a helpful assistant that answers questions clearly.",
  provider: "anthropic",
  model: "claude-sonnet-4-6",
  apiKey: "${vault:my-anthropic-key}"
)

curl -X POST http://localhost:7070/administration/agents/setup \
  -H "Content-Type: application/json" \
  -d '{
    "agentName": "My first agent",
    "systemPrompt": "You are a helpful assistant that answers questions clearly.",
    "provider": "anthropic",
    "model": "claude-sonnet-4-6",
    "apiKey": "${vault:my-anthropic-key}"
  }'

This creates the rules, LLM config, workflow, agent, and deploys it, all in one step.

Prefer a conversation or a form? A fresh install starts with no agents deployed. Open the Platform Operator at http://localhost:7070/manage/operator and describe the agent you want, with every change waiting for your approval, or fill in the agent wizard at http://localhost:7070/manage/agents/wizard.

5. Chat with Your Agent

chat_with_agent(agentId: "<your-agent-id>", message: "Hello! What can you do?")

# Start a conversation and send a message
curl -X POST http://localhost:7070/agents/<your-agent-id>/start \
  -H "Content-Type: application/json" \
  -d '{"input": "Hello! What can you do?"}'

Installer Options

The install script supports flags for automated and customized setups:

• --defaults: All defaults, no prompts
• --db=postgres: Use PostgreSQL instead of MongoDB
• --with-auth: Enable Keycloak authentication
• --with-monitoring: Add Prometheus and Grafana monitoring
• --full: Everything enabled (database + auth + monitoring)
• --eddi-version=6.4.0: Pin a specific EDDI release
• --local: Build Docker image from local source (for contributors)

Updating EDDI

The installer creates an eddi CLI wrapper. To pull the latest image and restart:

eddi update

If the CLI is not available, run from your install directory (~/.eddi):

cd ~/.eddi
docker compose --env-file .env -f docker-compose.yml pull
docker compose --env-file .env -f docker-compose.yml up -d

Kubernetes Deployment

Deploy to Kubernetes with a single command:

kubectl apply -f https://raw.githubusercontent.com/labsai/EDDI/main/k8s/quickstart.yaml

Kustomize overlays and the Helm chart (2.0.0) are also available for MongoDB, PostgreSQL, auth, monitoring, and production hardening (HPA, PDB, NetworkPolicy). See the Kubernetes Guide.