Application Tracker MCP

A privacy-first Model Context Protocol server for managing job, fellowship, and graduate-school applications locally.

It gives an MCP client a durable local workspace for:

• saving a job description and application status;
• comparing a private factual profile to a role without inventing experience;
• creating editable LaTeX CV and cover-letter starters;
• producing an interview-prep scaffold;
• discovering roles from opt-in public Greenhouse, Lever, and Ashby job-board APIs.

It does not submit applications, scrape logged-in sites, bypass CAPTCHAs/rate limits, or send data to a hosted service.

Why an MCP server?

An LLM is useful for interpreting a job description and drafting language. It should not be the database of record or silently decide facts about a candidate. This server keeps the repeatable operations local and explicit:

Private profile + job description
              ↓
      MCP tools: save / analyse / scaffold / track
              ↓
  Agent drafts wording from factual evidence
              ↓
       Human reviews, edits, and submits

The server owns tracking and document scaffolding. The MCP client owns conversational reasoning. The user owns the final claims and submission.

Privacy model

The public repository contains no applicant data. It includes only fictional examples.

• Configure APPLICATION_TRACKER_ROOT to a private local directory.
• Keep profiles, real application records, PDFs, job descriptions, and notes outside the repository or in ignored directories.
• The server accepts only paths relative to APPLICATION_TRACKER_ROOT; it rejects absolute paths and path traversal.
• Do not commit the configured data workspace. The included .gitignore ignores data/, applications/, private/, PDFs, and LaTeX build output.

Read SECURITY.md before using the server with sensitive information.

Quick start

Requires Python 3.10+ and the official Python MCP SDK.

git clone https://github.com/YOUR_GITHUB_USERNAME/application-tracker-mcp.git
cd application-tracker-mcp
python -m venv .venv
. .venv/bin/activate
pip install -e .

# Pick a private directory that is NOT inside the Git checkout.
export APPLICATION_TRACKER_ROOT="$HOME/.local/share/application-tracker"
application-tracker-mcp

The server uses MCP's standard stdio transport. The client launches it as a subprocess and communicates using JSON-RPC over standard input/output. See the MCP transport specification.

Example client configuration

Use a client configuration equivalent to the following (adapt the absolute paths):

{
  "mcpServers": {
    "application-tracker": {
      "command": "/absolute/path/to/application-tracker-mcp/.venv/bin/application-tracker-mcp",
      "env": {
        "APPLICATION_TRACKER_ROOT": "/absolute/private/path/application-tracker-data"
      }
    }
  }
}

MCP tools

Tool	Purpose
create_application	Saves a private application record and its job description.
list_applications	Lists records, optionally by status.
update_application_status	Tracks drafting, applied, interview, offer, rejected, and closed states.
analyse_application_fit	Matches only declared private profile skills/evidence against the saved JD.
render_application_drafts	Writes editable LaTeX CV and cover-letter starters plus a tailoring brief.
create_interview_prep	Creates a factual interview-practice scaffold.
compile_application_tex	Runs Tectonic on a generated .tex file without using a shell.
discover_public_jobs	Fetches roles from public Greenhouse, Lever, or Ashby APIs.

Example workflow

1. Copy the fictional profile example into your private data workspace and replace it with your own verified facts.
2. Ask an MCP client to call create_application with the job description.
3. Call analyse_application_fit with a relative profile path such as private/profile.json.
4. Ask the agent to write a factual tailoring brief using the returned evidence.
5. Call render_application_drafts to create local, editable .tex files.
6. Review and edit the files. If Tectonic is installed, call compile_application_tex.
7. Use update_application_status as the process progresses.
8. Before an interview, call create_interview_prep with only truthful highlights.

The examples/ directory is documentation only. It is deliberately fictional and does not demonstrate a real applicant.

Public job discovery

The repository has a small safe subset of the larger job-discovery concept. It supports only public APIs:

discover_public_jobs(provider="greenhouse", board="example-board", location_contains="Berlin")
discover_public_jobs(provider="lever", board="example-company")
discover_public_jobs(provider="ashby", board="example-company")

It intentionally does not scrape LinkedIn, StepStone, Xing, authenticated pages, or sites with CAPTCHAs. It does not apply to jobs.

LaTeX notes

render_application_drafts creates generic, editable LaTeX starters. The server never writes a real applicant's data into this repository; it only writes into your private workspace at runtime.

If Tectonic is on PATH, compile_application_tex can compile an artifact safely using argument lists, not a shell. Otherwise, compile the .tex file with your preferred local LaTeX workflow.

Development

python -m unittest discover -s tests -v
python -m compileall src tests

The server targets the official Python MCP SDK v2 (mcp>=2,<3), whose high-level server class is MCPServer. SDK migration notes

Project status

This is an early local-first foundation. Good next additions are encrypted-at-rest user storage, a richer document-template system, more public ATS connectors, and client-specific installation guides.