
AI Meta MCP Server
Enables AI models to dynamically create and execute their own custom tools at runtime, supporting JavaScript, Python, and Shell with sandboxed execution and human approval requirements.
Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.
What it does
- Create custom tools dynamically during AI conversations
- Execute JavaScript, Python, and Shell code in sandboxed environments
- Store and load custom tool definitions between sessions
- Manage tool registry with list, update, and delete operations
- Require human approval for tool creation and execution
- Configure execution permissions per runtime environment
Best for
About AI Meta MCP Server
AI Meta MCP Server is a community-built MCP server published by alxspiker that provides AI assistants with tools and capabilities via the Model Context Protocol. AI Meta MCP Server — AI tool builder for autonomous AI tools and AI function platform: create JS, Python & Shell tools w It is categorized under ai ml, developer tools.
How to install
You can install AI Meta MCP Server in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
License
AI Meta MCP Server is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
AI Meta MCP Server
A dynamic MCP server that allows AI models to create and execute their own custom tools through a meta-function architecture. This server provides a mechanism for AI to extend its own capabilities by defining custom functions at runtime.
Features
- Dynamic Tool Creation: AI can define new tools with custom implementations
- Multiple Runtime Environments: Support for JavaScript, Python, and Shell execution
- Sandboxed Security: Tools run in isolated sandboxes for safety
- Persistence: Store and load custom tool definitions between sessions
- Flexible Tool Registry: Manage, list, update, and delete custom tools
- Human Approval Flow: Requires explicit human approval for tool creation and execution
Security Considerations
⚠️ WARNING: This server allows for dynamic code execution. Use with caution and only in trusted environments.
- All code executes in sandboxed environments
- Human-in-the-loop approval required for tool creation and execution
- Tool execution privileges configurable through environment variables
- Audit logging for all operations
Installation
npm install ai-meta-mcp-server
Usage
Running the server
npx ai-meta-mcp-server
Running with Docker
# Build the Docker image
docker build -t ai-meta-mcp-server .
# Run the container
docker run --rm -i ai-meta-mcp-server
# Run with custom configuration and persistent storage
docker run --rm -i \
-e ALLOW_PYTHON_EXECUTION=true \
-e ALLOW_SHELL_EXECUTION=false \
-v $(pwd)/data:/app/data \
ai-meta-mcp-server
Configuration
Environment variables:
ALLOW_JS_EXECUTION: Enable JavaScript execution (default: true)ALLOW_PYTHON_EXECUTION: Enable Python execution (default: false)ALLOW_SHELL_EXECUTION: Enable Shell execution (default: false)PERSIST_TOOLS: Save tools between sessions (default: true)TOOLS_DB_PATH: Path to store tools database (default: "./tools.json")
Running with Claude Desktop
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"ai-meta-mcp": {
"command": "npx",
"args": ["-y", "ai-meta-mcp-server"],
"env": {
"ALLOW_JS_EXECUTION": "true",
"ALLOW_PYTHON_EXECUTION": "false",
"ALLOW_SHELL_EXECUTION": "false"
}
}
}
}
Tool Creation Example
In Claude Desktop, you can create a new tool like this:
Can you create a tool called "calculate_compound_interest" that computes compound interest given principal, rate, time, and compounding frequency?
Claude will use the define_function meta-tool to create your new tool, which becomes available for immediate use.
Architecture
The server implements the Model Context Protocol (MCP) and provides a meta-tool architecture that enables AI-driven function registration and execution within safe boundaries.
License
MIT
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