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Wingmen

Think wingmen as a AI asistant for non devs, it builds upon LLMs as core orchestrators and gets tools from mcp servers.

Code Video Cerebral Valley

Core trick

Embeds MCP tool descriptions and retrieves the top matches per request at runtime so no manual tool configuration is needed.

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Description

Think wingmen as a AI asistant for non devs, it builds upon LLMs as core orchestrators and gets tools from mcp servers. But unlike dev platforms like cursor or claude, where you have to configure tools independently, it uses a RAG on the available tools to pick up tools dynamically on runtime and execute the task. This enables 0 configuration workflows. For example, if you wanted to get prepared for your daily schedule, it would use google calendar to fetch your schedule and use LLMs intelligence to plan your day. Then you can schedule the same task to be ran daily at 8 am in the morning.
universal-mcp/applications★ 23 forksPythonMITCreated Sep 6, 2025 · last push Apr 9, 2026

README excerpt

# Universal MCP Applications

**A collection of 80+ installable application wrappers for the Universal MCP framework.**

This package provides a unified collection of all individual Universal MCP applications. It allows you to install every available tool at once and use them either as Python libraries in your own code.

## Installation

It is recommended to use `uv` for faster installation.

```bash
# Recommended using uv
uv pip install universal-mcp-applications

# Or using standard pip
pip install universal-mcp-applications
```

## Usage

The primary way to use the tools in this package is give below :-

### 1. As a Library

Each application can be imported and used directly in your Python projects. This is useful for integrating with other scripts or building more complex workflows.

**Example:**

```python
from universal_mcp_applications.falai import FalaiApp
from universal_mcp.utils import process_output

# Instantiate the application
# You may need to provide credentials via an integration
app = FalaiApp() 

# Call a method
result = app.some_method(param1="value1")

# Process and print the output
process_output(result)
```

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