Claude MCP Job Assistant
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Claude MCP Job Assistantrecommend jobs based on my resume"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Claude MCP Job Assistant
Overview
Claude MCP Job Assistant is a production-ready MCP (Model Context Protocol) server designed to demonstrate how Tools, Resources, and Prompts can be orchestrated to build an intelligent job search assistant.
The project uses Claude Desktop as the MCP Host/Client and exposes a complete ecosystem for:
Searching job opportunities.
Saving interesting positions.
Performing labor market analysis.
Receiving personalized recommendations based on a resume.
Generating matching reports between a resume and saved jobs.
This project provides a practical introduction to the Model Context Protocol and illustrates how modern AI assistants can leverage MCP capabilities to deliver contextual and personalized experiences.
Related MCP server: jobkit-mcp
Features
MCP-compliant server implementation.
Integration with Claude Desktop.
Intelligent job search.
Job bookmarking and persistence.
Resume-based recommendations.
Labor market analysis.
Matching reports generation.
Modular architecture using MCP Tools, Resources, and Prompts.
Production-ready setup with
uv.
Architecture
The MCP server is organized around the three core MCP primitives:
Tools
Tool | Description |
| Retrieves job offers using an external API. |
| Saves selected jobs in a structured format. |
Resources
Resource | Description |
| Loads the user's resume. |
| Loads previously saved jobs. |
Prompts
Prompt | Description |
| Analyzes labor market trends. |
| Suggests jobs, skills, and companies based on the user's resume. |
| Generates a report comparing saved jobs with the user's resume. |
Workflow
User
↓
Claude Desktop (MCP Host)
↓
MCP Job Assistant Server
├── Tools
│ ├── search_jobs()
│ └── save_job()
│
├── Resources
│ ├── resume://default
│ └── jobs://saved
│
└── Prompts
├── analyze_job_market()
├── personalized_job_recommender()
└── create_match_report()
↓
Generated ResponseTechnologies Used
Python
Model Context Protocol (MCP)
Claude Desktop
UV
External Job APIs
PDF Processing
Installation
1. Clone the Repository
git clone https://github.com/eric623/Claude-MCP-Job-Assistant.git
cd Claude-MCP-Job-Assistant2. Install Dependencies
This project uses uv for dependency management.
uv syncAt this stage, the MCP server is ready to be launched by Claude Desktop.
Claude Desktop Configuration
Step 1: Install Claude Desktop
Download and install Claude Desktop from Anthropic.
Step 2: Open Developer Settings
Navigate to:
Settings → Developer → Edit ConfigThis opens the claude_desktop_config.json file.
Step 3: Add the MCP Server
Add the following configuration:
{
"mcpServers": {
"mcp_job": {
"command": "uv",
"args": [
"--directory",
"PATH_TO_PROJECT_DIRECTORY",
"run",
"server.py"
]
}
}
}Replace
PATH_TO_PROJECT_DIRECTORYwith the absolute path to your local project folder.
Adding Your Resume
Place your CV inside the resume directory.
The file must be named exactly:
resume.pdfExample:
Claude-MCP-Job-Assistant/
│
└── resume/
└── resume.pdfImportant: Resume-based recommendations and matching reports require this file.
Launching the MCP Server
After saving the configuration:
Completely close Claude Desktop.
Reopen Claude Desktop.
You should now see:
mcp_job (Running)in the Developer panel.
MCP Concepts Demonstrated
MCP Tools
MCP Resources
MCP Prompts
Claude Desktop Integration
Context-Aware AI Systems
Intelligent Job Search
External API Consumption
Personalized Recommendations
Modular MCP Server Design
Why This Project?
This project was built to explore and demonstrate the capabilities of the Model Context Protocol (MCP) by implementing a realistic use case centered around job exploration and career assistance.
It highlights how MCP enables:
Context-aware assistants.
Modular architectures.
Tool orchestration.
Resource management.
Prompt engineering.
Intelligent interactions between users and AI systems.
Author
AKAKPO Koffi Moïse
Interested in Agentic AI, Multi-Agent Systems, and Applied Artificial Intelligence.
Claude MCP Job Assistant demonstrates how the Model Context Protocol can be leveraged to build intelligent, modular, and extensible assistants through the coordinated use of Tools, Resources, and Prompts.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Tools
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