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

hljs language-php

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)

Quick Start

1. Install dependencies

hljs language-bash

cd wave-mcp-server
npm install

2. Set environment variables

hljs language-bash

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

hljs language-bash

npm run build

4. Configure in Cursor

Add to ~/.cursor/mcp.json:

hljs language-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_entities`	List all entity schemas
`create_entity`	Create a new entity schema
`read_records`	Read/filter/sort/paginate records
`create_records`	Create one or more records
`update_records`	Update records matching a filter
`delete_records`	Delete records matching a filter
`aggregate_records`	Run MongoDB aggregation pipelines
`call_function`	Call any deployed backend function
`upload_file`	Upload a file to public storage

Layer 2: Theta Compute (8 tools)

Tool	Description
`theta_list_models`	List available AI models
`theta_run_inference`	Run AI inference on Theta EdgeCloud
`theta_check_gpu_status`	Check running GPU instances
`theta_estimate_cost`	Estimate TFUEL cost for a job
`theta_deploy_contract`	Deploy a smart contract to Theta mainnet
`theta_read_contract`	Call a view function on a deployed contract
`theta_get_balance`	Get wallet TFUEL and WAVE token balances
`theta_get_transaction`	Fetch transaction details by hash

Layer 3: Wave OS Intelligence (8 tools)

Tool	Description
`wave_morning_briefing`	Get aggregated daily briefing
`wave_triage`	Scan for urgent items across all entities
`wave_follow_up_scan`	Check overdue/due/upcoming follow-ups
`wave_meeting_prep`	Get preparation context for a meeting
`wave_save_memory`	Save a memory (auto-categorized)
`wave_recall_memory`	Search memories by keyword/category
`wave_delegate_subagent`	Delegate a task to a sub-agent
`wave_chat`	Chat with Wave OS AI Assistant

Demo Flows

Flow 1: Full-Stack Build

hljs language-vbnet

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 data

Flow 2: Intelligence Layer

hljs language-vbnet

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 assigned

Flow 3: Blockchain + Data

hljs language-vbnet

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

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

hljs language-php

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)

Quick Start

1. Install dependencies

hljs language-bash

cd wave-mcp-server
npm install

2. Set environment variables

hljs language-bash

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

hljs language-bash

npm run build

4. Configure in Cursor

Add to ~/.cursor/mcp.json:

hljs language-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_entities`	List all entity schemas
`create_entity`	Create a new entity schema
`read_records`	Read/filter/sort/paginate records
`create_records`	Create one or more records
`update_records`	Update records matching a filter
`delete_records`	Delete records matching a filter
`aggregate_records`	Run MongoDB aggregation pipelines
`call_function`	Call any deployed backend function
`upload_file`	Upload a file to public storage

Layer 2: Theta Compute (8 tools)

Tool	Description
`theta_list_models`	List available AI models
`theta_run_inference`	Run AI inference on Theta EdgeCloud
`theta_check_gpu_status`	Check running GPU instances
`theta_estimate_cost`	Estimate TFUEL cost for a job
`theta_deploy_contract`	Deploy a smart contract to Theta mainnet
`theta_read_contract`	Call a view function on a deployed contract
`theta_get_balance`	Get wallet TFUEL and WAVE token balances
`theta_get_transaction`	Fetch transaction details by hash

Layer 3: Wave OS Intelligence (8 tools)

Tool	Description
`wave_morning_briefing`	Get aggregated daily briefing
`wave_triage`	Scan for urgent items across all entities
`wave_follow_up_scan`	Check overdue/due/upcoming follow-ups
`wave_meeting_prep`	Get preparation context for a meeting
`wave_save_memory`	Save a memory (auto-categorized)
`wave_recall_memory`	Search memories by keyword/category
`wave_delegate_subagent`	Delegate a task to a sub-agent
`wave_chat`	Chat with Wave OS AI Assistant

Demo Flows

Flow 1: Full-Stack Build

hljs language-vbnet

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 data

Flow 2: Intelligence Layer

hljs language-vbnet

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 assigned

Flow 3: Blockchain + Data

hljs language-vbnet

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.

wave-mcp-server

Wave OS MCP Server

Architecture

Quick Start

1. Install dependencies

2. Set environment variables

3. Build

4. Configure in Cursor

5. Run in Cursor

Available Tools (21 total)

Layer 1: Base44 Backend (9 tools)

Layer 2: Theta Compute (8 tools)

Layer 3: Wave OS Intelligence (8 tools)

Demo Flows

Flow 1: Full-Stack Build

Flow 2: Intelligence Layer

Flow 3: Blockchain + Data

Competition Pitch

License

Similar Packages

wave-mcp-server

Wave OS MCP Server

Architecture

Quick Start

1. Install dependencies

2. Set environment variables

3. Build

4. Configure in Cursor

5. Run in Cursor

Available Tools (21 total)

Layer 1: Base44 Backend (9 tools)

Layer 2: Theta Compute (8 tools)

Layer 3: Wave OS Intelligence (8 tools)

Demo Flows

Flow 1: Full-Stack Build

Flow 2: Intelligence Layer

Flow 3: Blockchain + Data

Competition Pitch

License

Similar Packages