https://github.com/simagix/vector-openai-mcp
Demo on Vector Search, OpenAI, and MCP
https://github.com/simagix/vector-openai-mcp
Last synced: 10 months ago
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Demo on Vector Search, OpenAI, and MCP
- Host: GitHub
- URL: https://github.com/simagix/vector-openai-mcp
- Owner: simagix
- Created: 2025-08-04T20:34:59.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-08-10T10:31:29.000Z (10 months ago)
- Last Synced: 2025-08-10T12:27:30.471Z (10 months ago)
- Language: Python
- Size: 9.77 KB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Vector Search + OpenAI MCP Demo
This project demonstrates how to implement vector search using Sentence-Transformers locally and on MongoDB Atlas, followed by integrating OpenAI’s Model Context Protocol (MCP) for intelligent routing and semantic querying. For more details, see the [Gen AI & Vector Search](https://sites.google.com/simagix.com/genai-vector-search) guide.
## Table of Contents
- [Vector Search + OpenAI MCP Demo](#vector-search--openai-mcp-demo)
- [Table of Contents](#table-of-contents)
- [Overview](#overview)
- [Setup](#setup)
- [Environment Variables](#environment-variables)
- [Components](#components)
- [🔹 `load_data.py`](#-load_datapy)
- [🔹 `sbert_vector_search.py`](#-sbert_vector_searchpy)
- [🔹 `atlas_vector_search.py`](#-atlas_vector_searchpy)
- [🔹 `mcp_server.py` \& `mcp_client.py`](#-mcp_serverpy--mcp_clientpy)
- [🔹 `mcp_news_server.py`](#-mcp_news_serverpy)
- [🔹 `openai_client.py`](#-openai_clientpy)
- [Run Instructions](#run-instructions)
- [Testing](#testing)
- [License](#license)
---
## Overview
The project begins with populating data from the AG News dataset and showcases:
1. **Local Vector Search** using [Sentence-Transformers](https://www.sbert.net/)
2. **MongoDB Atlas Vector Search** using `$vectorSearch`
3. **Intent Routing via MCP** to direct user input using semantic understanding
4. **OpenAI Integration** with Azure to power a natural language interface
---
## Setup
Install dependencies:
```bash
pip install -r requirements.txt
```
---
## Environment Variables
You can set environment variables in a `.env` file or export them in your shell. Required variables include:
- `MONGO_URL`
- `AZURE_OPENAI_API_KEY`
- `AZURE_OPENAI_ENDPOINT`
- `OPENAI_API_KEY`
- `USE_AZURE_OPENAI` (set to `true` to use Azure OpenAI)
Example for Azure OpenAI (if using `mcp_news_server.py`):
```bash
export AZURE_OPENAI_API_KEY=your_key
export AZURE_OPENAI_ENDPOINT=https://your-endpoint.openai.azure.com/
```
---
## Components
### 🔹 `load_data.py`
Populates the `ag_news` collection with news data for use in local and Atlas vector search.
### 🔹 `sbert_vector_search.py`
Performs vector search locally using Sentence-Transformers (`all-MiniLM-L6-v2`).
### 🔹 `atlas_vector_search.py`
Uses MongoDB Atlas's `$vectorSearch` operator to run vector search on the cloud.
### 🔹 `mcp_server.py` & `mcp_client.py`
Demonstrates a simple MCP-based server and client setup to handle tool routing using user intent.
### 🔹 `mcp_news_server.py`
Extends `mcp_server` by integrating Azure OpenAI to route user input intelligently and combine it with local vector search.
### 🔹 `openai_client.py`
Provides a unified client for querying OpenAI or Azure OpenAI models.
---
## Run Instructions
1. **Populate the database**:
```bash
python load_data.py
```
2. **Run local vector search demo**:
```bash
python sbert_vector_search.py
```
3. **Run Atlas vector search demo**:
```bash
python atlas_vector_search.py
```
4. **Start the MCP server**:
```bash
python mcp_server.py
```
5. **Send a query**:
```bash
python mcp_client.py
```
6. **Optional**: For the AI-powered experience:
```bash
python mcp_news_server.py
```
---
## Testing
To run all unit and integration tests:
```bash
python -m unittest discover -s tests
```
---
## License
Licensed under the Apache License, Version 2.0. See the [LICENSE](LICENSE) file for more information.