Supercharge Your Job Search: Automate with MCP, Astra, Langflow and Arize
on May 4, 2025
Are you struggling to find the right job? Well, it's time to level up your job search with technology! Today, I'm going to show you how to enhance your job search by building an MCP server and automating the entire process with cutting-edge tools like Astra and Arize.
By the end of this post, you'll understand how to set up your own server to search for companies that align with your interests and even experiment with AI agents to make your search more efficient and tailored to your needs. Let's dive in! 🎯
🏢 Using the "Recherche d'Entreprise" API
The Recherche d'Entreprise API, offered by the French government, is an open-source tool you can leverage to gather data on thousands of businesses. By integrating this into your search, you can refine your results based on criteria like postal code, department, and region. 🌎
This API is an excellent resource for anyone who's in search of potential employers or clients. It's a fast and efficient way to access public business data. To get started, you can access the API here. 🔗
🤖 Why Use MCP for Job Searching?
What is MCP (Model Context Protocol)? Simply put, MCP is an open protocol that turns traditional LLM (Large Language Models) chatbots into intelligent agents capable of performing specific tasks based on user input. By creating your own MCP server, you can prompt your IDE (Integrated Development Environment) to help with tasks like job searching while you code! How cool is that? 💡
In this step, you'll configure a simple MCP Server for Job Searching, which can handle requests from your job search queries. The beauty of MCP is that it works seamlessly with various tools to retrieve precise information about companies you're interested in. You can even specialize your searches to find businesses that match your specific criteria.
To set up your own MCP server, follow the step-by-de in this tutorial from Jolicode. 🔧
🔧 Integrating Astra for Data Storage
Once you've set up your MCP server, it's time to integrate AstraDB. AstraDB is a cloud-native database solution that allows you to easily store, manage, and query large datasets.
To make your searches even more efficient, you can vectorize your documents using Astra, so that each search query returns highly relevant results. All of the business data retrieved from the Recherche d'Entreprise API can be stored in AstraDB. 📊
To start using AstraDB, sign up here and connect it with your MCP server. You'll need to add your Astra API keys to your project for it to work seamlessly.
📈 Monitoring with Arize
Once your MCP server is up and running with Astra, it's time to monitor the performance of your AI models using Arize. Arize is a monitoring platform designed for AI models, helping you track performance and improve your models over time. 🌟
Arize makes it easy to see how well your search models are performing, allowing you to adjust parameters and experiment with different AI agents. This is crucial to ensure that your search queries are being processed as accurately and efficiently as possible. 🔍
To sign up for Arize and start monitoring your models, visit this link. 📱
🤖 Experimenting with Langflow for RAG Models
Now, let's take it a ther by integrating Langflow. Langflow is a tool for building RAG (Retrieve, Augment, Generate) models, which allow you to combine the strengths of large language models (LLMs) with external data sources, like your Astra database.
With Langflow, you can create intelligent chatbots capable of answering specific queries based on your job search results. You can integrate it with the Astra database and Arize to track performance and improve accuracy.
Follow the Langflow setup guide to integrate it into your system. 🧑💻
🏁 Putting It All Together
At this point, you have:
- MCP Server to handle job search queries.
- AstraDB to store and vectorize company data.
- Arize to monitor and improve your AI models.
- Langflow to create advanced RAG models for smarter, more efficient searches.
All of these tools combined will supercharge your job search, allowing you to focus on high-priority companies and specific roles, while automating much of the data retrieval and analysis process. 🔄
🧪 Checkout the source code
You can checkout the source code of this article on Github here
🚀 Want to build your own workflows?
Let's take your career to the next level with technology! 🚀
Feel free to reach out for any questions, and don't forget to share this with friends who might benefit from automating their job search. Happy vibe coding! 🎉
Ressources
- API Recherche d’Entreprises : https://www.data.gouv.fr/fr/dataservices/api-recherche-dentreprises
- rag-playground in Python : https://github.com/acantarero/rag-playground
- Real-time document Q&A using Pulsar, Cassandra, and langchain : https://github.com/acantarero/wikipedia_demo
- 📨 Build an Email-Powered AI Agent (using Langflow and Twilio) : https://www.youtube.com/watch?v=Nkek6TCCUzE
- Arize AI : https://github.com/Arize-ai
- Phoenix : https://github.com/Arize-ai/phoenix
- Arize Python SDK Reference : https://arize-client-python.readthedocs.io/en/latest/
- Create an experiment with Arize : https://github.com/datastaxdevs/build_accurate_ai_langflow_arize/blob/main/langflow_arize.ipynb
- How to Build a Real-World RAG Chatbot That Actually Works (N8N + Vectorize) : https://www.youtube.com/watch?v=o6QHoUXXnaM
- How To Get The Most Out Of Vibe Coding | Startup School : https://www.youtube.com/watch?v=BJjsfNO5JTo
- Background credit Slidebean : https://unsplash.com/photos/turned-on-pendant-lamps-TpGIpUF67po