Code Mode Bridge

Code Mode Bridge

An MCP server that aggregates multiple upstream MCP tools into a single 'codemode' tool for unified orchestration and execution. It enables agents to run generated code in an isolated sandbox to interact with various connected services through a single interface.

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README

Code Mode Bridge

An MCP (Model Context Protocol) server that connects to upstream MCP servers and exposes all their tools through a single codemode tool for unified orchestration and execution.

Features

  • Multi-server bridging: Connect to multiple upstream MCP servers simultaneously
  • Tool aggregation: Exposes all upstream tools through a single codemode tool
  • Dynamic discovery: Auto-generated tool descriptions show agents exactly what's available
  • Namespaced tools: Tools are automatically namespaced by server (e.g., kubernetes__pods_list)
  • Sandbox execution: Code runs in isolated vm2 sandbox with 30-second timeout
  • CLI management: Easy command-line interface for server configuration
  • npx compatible: Run directly with npx codemode-bridge

Quick Start

Installation

npm install -g codemode-bridge
# or use directly with npx
npx codemode-bridge --help

Basic Usage

List configured servers:

codemode-bridge config list

Add a new server:

codemode-bridge config add kubernetes --type stdio --command "npx" --args "-y,kubernetes-mcp-server@latest"

Start the bridge (loads all configured servers):

codemode-bridge run

Load specific servers:

codemode-bridge run --servers kubernetes,time

Configuration

Servers are stored in ~/.config/codemode-bridge/mcp.json:

{
  "servers": {
    "kubernetes": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "kubernetes-mcp-server@latest"]
    },
    "time": {
      "type": "stdio",
      "command": "uvx",
      "args": ["mcp-server-time"]
    },
    "example-http": {
      "type": "http",
      "url": "https://example.com/mcp"
    }
  }
}

Server Types

  • stdio: Execute a command that runs an MCP server via stdin/stdout
  • http: Connect to an HTTP-based MCP server

How It Works

  1. Connection: Connects to all configured upstream MCP servers using Vercel AI SDK's MCP client
  2. Tool Collection: Gathers tools from all servers via the MCP protocol
  3. Tool Wrapping: Uses @cloudflare/codemode SDK to wrap all tools
  4. Code Generation: SDK auto-generates TypeScript type definitions for tools
  5. Exposure: Exposes a single codemode MCP tool that agents can call
  6. Execution: Runs agent-generated code in isolated vm2 sandbox with tool access

Tool Discovery

When agents query the codemode tool schema, the auto-generated description includes:

  • TypeScript type definitions for all available tools
  • Complete function signatures
  • Tool descriptions and parameter documentation
  • Example usage patterns

This allows agents to discover the complete API surface by reading the tool description.

CLI Commands

# Start the bridge (default command)
codemode-bridge run [options]
  --servers <names>  Comma-separated list of servers to load
  --config <path>    Custom config file path

# Configuration management
codemode-bridge config list              # Show all configured servers
codemode-bridge config show <name>       # Show specific server config
codemode-bridge config add <name>        # Add new server
codemode-bridge config remove <name>     # Remove server
codemode-bridge config edit <name>       # Edit server config
codemode-bridge config info              # Show config file location

Examples

Using with mcporter

# Start the bridge
codemode-bridge run --servers kubernetes &

# List available tools
mcporter list codemode-bridge --schema

# Call the codemode tool
mcporter call codemode-bridge.codemode code='async () => {
  const namespaces = await codemode.kubernetes__namespaces_list({});
  return namespaces;
}'

Using with Claude or other LLMs

When connected as an MCP server, Claude can:

  1. See the codemode tool in its tool list
  2. Read auto-generated documentation about all available tools
  3. Write code that orchestrates multiple tools across servers
  4. Execute the code in an isolated sandbox

Example code an LLM might write:

// Get current time and convert to different timezone
const now = await codemode.time__get_current_time({ timezone: "America/New_York" });
const singapore = await codemode.time__convert_time({
  source_timezone: "America/New_York",
  target_timezone: "Asia/Singapore",
  time: now
});
return { newYork: now, singapore };

Architecture

┌─────────────────────────────────────────────────────────┐
│           MCP Clients (Claude, mcporter, etc)           │
└────────────────────┬────────────────────────────────────┘
                     │ MCP Protocol
                     │
┌────────────────────▼────────────────────────────────────┐
│         Code Mode Bridge (MCP Server)                   │
│  ┌──────────────────────────────────────────────────┐   │
│  │  Single "codemode" Tool                          │   │
│  │  - Auto-generated type definitions               │   │
│  │  - Sandbox code execution                        │   │
│  │  - Tool orchestration                            │   │
│  └──────────────────────────────────────────────────┘   │
└────────────────────┬────────────────────────────────────┘
                     │ @ai-sdk/mcp (MCP Client)
        ┌────────────┼────────────┬─────────────┐
        │            │            │             │
   ┌────▼─────┐ ┌───▼────┐ ┌────▼──────┐ ┌───▼──────┐
   │Kubernetes │ │  Time  │ │ GitLab    │ │ Memory   │
   │  Server   │ │ Server │ │  Server   │ │  Server  │
   └──────────┘ └────────┘ └───────────┘ └──────────┘

Project Structure

src/
├── cli/
│   ├── index.ts              # CLI entry point (with #!/usr/bin/env node shebang)
│   ├── commands.ts           # Command implementations
│   └── config-manager.ts     # Configuration management
├── mcp/
│   ├── server.ts             # MCP server + upstream connections
│   ├── executor.ts           # VM2 sandbox executor implementation
│   ├── mcp-adapter.ts        # Protocol adapter (AI SDK Tool → MCP)
│   └── config.ts             # Configuration types
└── index.ts                  # Package main entry point

config/
└── mcporter.json             # mcporter client configuration

dist/                          # Compiled JavaScript (generated)
.gitignore                     # Git ignore patterns
package.json                   # NPM package configuration
tsconfig.json                  # TypeScript configuration
README.md                      # This file

Development

Build

npm run build

Test CLI locally

npm run dev:cli -- run --servers time
npm run dev:cli -- config list
npm run dev:cli -- config show kubernetes

Rebuild and test after changes

npm run build
npx codemode-bridge config list

Security

  • Sandboxed execution: Code runs in isolated vm2 environment
  • Timeout enforcement: 30-second limit prevents infinite loops
  • No network access: Sandbox cannot make direct HTTP requests
  • No file system access: Cannot read/write files on host
  • Tool isolation: Only tools from configured servers are accessible

Prebuilt Servers

The bridge comes pre-configured with popular MCP servers:

  • kubernetes - Kubernetes cluster operations
  • swf_gitlab - GitLab integration (with SWF instance)
  • time - Time operations and timezone conversion
  • memory - Knowledge graph memory system
  • code-sandbox - Sandboxed code execution
  • mcp-git - Git operations
  • sequential-thinking - Structured reasoning
  • atlassian_cloud - Atlassian cloud integration (HTTP)

Run codemode-bridge config list to see all available servers.

AI Generated Code Disclosure

For anyone wondering, yes, this is almost entirely AI generated code. Though I consider it of fairly low risk given that it's sole purpose is to

  1. Run JS code in a VM2 environment.
  2. Bridge MCP servers to the VM2 sandbox.
  3. Most of this is built on top of existing libraries.

I have not (yet) tested this extensively to see what the VM2 sandbox capabilities are. This is more of an experiment I had going in the background during the workday to see if I could get cloudflare's Code Mode to work... without paying for workers.

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