Five steps from zero to a fully connected AI memory layer for your job search. Takes about five minutes.
Open Terminal and check if Python is already installed:
python3 --version
If you see "command not found", download Python from python.org/downloads and install it.
git clone https://github.com/JustLikeFrank3/jobContextMCP
cd jobContextMCP
python3 -m venv .venv
.venv/bin/pip install -r requirements.txt
cp config.example.json config.json
Open config.json in any text editor. Fill in your name, email, phone, and LinkedIn. The openai_api_key field can be left blank for now — it is only needed for RAG search features, not tone samples or outreach.
Make sure Claude Desktop is installed, then open this file in a text editor (create it if it does not exist):
Mac: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
Paste this, replacing the paths with wherever you cloned the repo:
{
"mcpServers": {
"jobContextMCP": {
"command": "/absolute/path/to/jobContextMCP/.venv/bin/python3",
"args": ["/absolute/path/to/jobContextMCP/server.py"],
"cwd": "/absolute/path/to/jobContextMCP"
}
}
}
Example on Mac: /Users/yourname/jobContextMCP/.venv/bin/python3
Restart Claude Desktop. Then in a Claude chat, say:
The tool will ask for your info and create all your data files from scratch.
Ask Claude to log_tone_sample from any message you write. After a few samples, get_tone_profile will reflect your voice and Claude can draft outreach in your register.