Wave OS MCP Server
Provides tools for interacting with MongoDB databases, including CRUD operations (create, read, update, delete records) and aggregation pipelines, via the Base44 backend.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Wave OS MCP Serverrun a triage scan on my projects"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Wave OS MCP Server
Three layers, one MCP server. Base44 handles your data, Theta handles your compute, and Wave OS handles your intelligence — all accessible from any AI coding assistant via the Model Context Protocol.
Built by xBuildy for the Base44 Dev Build-Off — July 2026.
Architecture
Cursor / Claude Code / Any MCP Client
│
▼
┌─────────────────────────────────────────┐
│ Wave OS MCP Server │
│ │
│ Layer 1: Base44 Backend (Data) │
│ ├─ Entity CRUD (create, read, update) │
│ ├─ Aggregation pipelines │
│ ├─ Backend function calls │
│ └─ File uploads │
│ │
│ Layer 2: Theta Compute (GPU + Chain) │
│ ├─ AI model inference │
│ ├─ GPU instance management │
│ ├─ Smart contract deployment │
│ ├─ Contract reads (view functions) │
│ ├─ Wallet balance queries │
│ └─ Transaction lookups │
│ │
│ Layer 3: Wave OS Intelligence │
│ ├─ Morning briefing (Chief of Staff) │
│ ├─ Triage scanning │
│ ├─ Follow-up tracking │
│ ├─ Meeting prep │
│ ├─ Memory save/recall │
│ ├─ Sub-agent delegation │
│ └─ Wave Assistant chat │
└─────────────────────────────────────────┘
│ │ │
▼ ▼ ▼
Base44 API Theta EdgeCloud Theta RPC
(database, (GPU compute, (blockchain,
functions, AI inference) smart contracts)
auth, files)Related MCP server: Tyra Advanced Memory MCP Server
Quick Start
1. Install dependencies
cd wave-mcp-server
npm install2. Set environment variables
export BASE44_APP_ID="your_app_id"
export BASE44_API_KEY="your_api_key"
export THETA_API_KEY="your_theta_api_key"
export THETA_PROJECT_ID="your_theta_project_id"3. Build
npm run build4. Configure in Cursor
Add to ~/.cursor/mcp.json:
{
"mcpServers": {
"wave-os": {
"command": "node",
"args": ["/path/to/wave-mcp-server/dist/index.js"],
"env": {
"BASE44_APP_ID": "your_app_id",
"BASE44_API_KEY": "your_api_key",
"THETA_API_KEY": "your_theta_api_key",
"THETA_PROJECT_ID": "your_theta_project_id"
}
}
}
}5. Run in Cursor
Restart Cursor, open a new chat, and the Wave OS tools will be available to the AI assistant.
Available Tools (21 total)
Layer 1: Base44 Backend (9 tools)
Tool | Description |
| List all entity schemas |
| Create a new entity schema |
| Read/filter/sort/paginate records |
| Create one or more records |
| Update records matching a filter |
| Delete records matching a filter |
| Run MongoDB aggregation pipelines |
| Call any deployed backend function |
| Upload a file to public storage |
Layer 2: Theta Compute (8 tools)
Tool | Description |
| List available AI models |
| Run AI inference on Theta EdgeCloud |
| Check running GPU instances |
| Estimate TFUEL cost for a job |
| Deploy a smart contract to Theta mainnet |
| Call a view function on a deployed contract |
| Get wallet TFUEL and WAVE token balances |
| Fetch transaction details by hash |
Layer 3: Wave OS Intelligence (8 tools)
Tool | Description |
| Get aggregated daily briefing |
| Scan for urgent items across all entities |
| Check overdue/due/upcoming follow-ups |
| Get preparation context for a meeting |
| Save a memory (auto-categorized) |
| Search memories by keyword/category |
| Delegate a task to a sub-agent |
| Chat with Wave OS AI Assistant |
Demo Flows
Flow 1: Full-Stack Build
You: "Create a Customer entity on my Base44 app"
AI: [calls create_entity] → Entity created with fields: name, email, status
You: "Add 5 sample customers"
AI: [calls create_records] → 5 records inserted
You: "Run sentiment analysis on these customers"
AI: [calls call_function to deploy sentiment function]
[calls theta_run_inference to analyze each customer]
[calls update_records to store sentiment scores]
You: "Show me the results"
AI: [calls read_records with fields projection] → Returns enriched dataFlow 2: Intelligence Layer
You: "What needs my attention today?"
AI: [calls wave_triage] → Returns: 2 calendar conflicts, 1 credit warning, 3 overdue tasks
You: "Save a note that Customer X is VIP"
AI: [calls wave_save_memory] → Memory saved with category "contact"
You: "Delegate a follow-up task to a sub-agent for Customer X"
AI: [calls wave_delegate_subagent] → Sub-agent spawned, task assignedFlow 3: Blockchain + Data
You: "Check the treasury wallet balance"
AI: [calls theta_get_balance] → Returns TFUEL and WAVE balances
You: "How many token holders do we have?"
AI: [calls read_records on TokenHolder entity] → Returns holder list
You: "Deploy a new TNT20 token contract"
AI: [calls theta_deploy_contract] → Contract deployed to mainnet
[calls create_records to log the deployment]Competition Pitch
Three layers, one MCP server. Base44 handles your data, Theta handles your compute, and Wave OS agent orchestration handles your intelligence. Your AI coding assistant can create an entity, deploy a function, provision a GPU, run inference, delegate a task to a sub-agent, get a morning briefing, and save a memory — all from a single prompt in Cursor.
License
MIT © xBuildy
Maintenance
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