Content
# Osmosis-MCP-4B
## [Blog Post](https://osmosis.ai/blog/applying-rl-mcp)
## Prerequisites
* Python 3.x
* uvx
* Access to a model server (e.g., running locally via vLLM/lm studio)
* API Keys for:
* Brave Search
* Google Maps
* AccuWeather
## Setup & Installation
1. **Clone the repository (if applicable):**
```bash
# git clone https://github.com/Gulp-AI/Osmosis-MCP-4B-demo
# cd Osmosis-MCP-4B-demo
```
2. **Install dependencies:**
It's recommended to use a virtual environment.
```bash
python -m venv .venv
source .venv/bin/activate # On Windows: .venv\Scripts\activate
pip install -r requirements.txt
```
3. **Set up Environment Variables:**
Create a `.env` file in the root of the project directory and add your API keys and model server configuration:
```env
BRAVE_API_KEY="your_brave_api_key"
GOOGLE_MAPS_API_KEY="your_google_maps_api_key"
ACCUWEATHER_API_KEY="your_accuweather_api_key"
APP_STYLE="gui" # or "tui"
```
if an api key is not provided, the tool will not be loaded.
The `main.py` script currently configures the model server URL directly. Ensure `http://localhost:1234/v1` is the correct endpoint for your Qwen model server (this is what lm studio uses).
4. **Serve local model:**
Use a tool like lm studio to provide a usable endpoint.
## Environment Variables
The application uses the following environment variables (loaded from a `.env` file):
* `BRAVE_API_KEY`: Your API key for Brave Search.
* `GOOGLE_MAPS_API_KEY`: Your API key for Google Maps.
* `ACCUWEATHER_API_KEY`: Your API key for AccuWeather.
* `APP_STYLE`: 'tui' or 'gui'
## Available Tools (MCP Servers)
The agent is configured to use the following tools via MCP:
* **Time:** Provides current time information.
* **Brave Search:** Enables web search capabilities.
* Requires: `BRAVE_API_KEY`
* **Fetch:** Fetches content from URLs.
* **Google Maps:** Provides location-based services.
* Requires: `GOOGLE_MAPS_API_KEY`
* **Weather:** Provides weather forecasts.
* Requires: `ACCUWEATHER_API_KEY`
* **Code Interpreter:** A built-in tool for executing Python code snippets.
These servers need to be running and accessible for the agent to utilize their respective functionalities. The `main.py` script provides the commands to start these MCP servers.
## How to Run Graphical User Interface (GUI):
This mode launches a web-based interface for interacting with the agent. This is the default mode.
```bash
python main.py
```
The web UI will be accessible at the address provided by the `WebUI` component upon startup (on `http://localhost:7860`).
---
Connection Info
You Might Also Like
MarkItDown MCP
Python tool for converting files and office documents to Markdown.
Filesystem
Model Context Protocol Servers
Sequential Thinking
Model Context Protocol Servers
mcp
The official svelte MCP for all your agentic needs.
task-orchestrator
Persistent AI memory for coding assistants - MCP server providing context...
claude_code-multi-AI-MCP
This MCP or multiple AI setup let claude code use Grok, Gemini and DeepSeek...