offer-quest mcp
# OfferQuest MCP Server (`mcp_j.py`)
[](https://glama.ai/mcp/connectors/space.hf.dexter3b-offerquest-mcp/offer-quest-mcp)
A fast, secure, and LLM-friendly Model Context Protocol (MCP) server that scrapes job listings from major platforms (LinkedIn, Indeed, Google) and converts them into structured Markdown format.
[](https://glama.ai/mcp/servers/theomatrix/Offer-Quest-MCP-)
## Features
- **Blazing Fast API Scraping:** Uses `python-jobspy` to pull latest jobs instantly without heavy browser automation overhead.
- **Multi-Search Support:** Automatically handles parallel searching for multiple comma-separated job titles and locations in a single unified run.
- **LLM-Optimized Output:** Jobs are formatted into a clean, easy-to-read Markdown table specifically designed for AI agents and LLMs to parse and understand securely.
- **Strict Security:**
- All user inputs are sanitized to drop executable scripts and strange characters (`_sanitize_text`).
- Limits max input length to prevent denial-of-service (DoS).
- Internal errors/stack traces are masked from the user to prevent data leakage.
- **Granular Targeting:**
- Dynamic **Country** selection explicitly prevents the APIs from serving out-of-bounds global results.
- "Max Hours Old" filter perfectly isolates ultra-fresh job postings.
## Installation
Ensure you have Python 3.10+ installed.
1. **Clone or navigate** to this project directory.
2. **Create a virtual environment** (Recommended):
```bash
python3 -m venv myenv
source myenv/bin/activate
```
3. **Install dependencies**:
```bash
pip install -r requirements.txt
```
## Usage
Start the server locally:
```bash
python3 mcp_j.py
```
- The server will boot up a local Gradio interface (usually `http://127.0.0.1:7860`).
- If you are plugging this into an MCP client, the endpoint is exposed at `/gradio_api/mcp/`.
## Deployment
Since the codebase is stateless and doesn't rely on background Playwright Chromium browsers, this script is highly viable for lightweight containerized deployments (Docker, Render, Heroku) or standard VPS setups.
**Security checklist completed for deployment:**
- [x] Catch-all error blocks to hide raw API tracebacks.
- [x] Built-in input sanitization using rigorous Regex.
- [x] Hard limits on payload size (`max_results=25` upper-bound).
*Note: For highest stability on cloud providers, ensure that the IP address you are querying from isn't strictly blacklisted by Indeed/LinkedIn.*TDQS
Scored across 1 tool
With only one tool, there is no possibility of ambiguity or overlap between tools. The single tool 'search_jobs' has a clearly defined and distinct purpose focused on job searching.
The single tool name 'search_jobs' follows a clear verb_noun pattern, and with only one tool, consistency is inherently perfect. There are no other tools to create inconsistency.
A single tool is too few for a server named 'offer-quest mcp', which implies a broader scope related to job offers or quests. This minimal toolset feels thin and incomplete for the apparent domain, limiting functionality to only searching without other operations like applying, tracking, or managing jobs.
The tool surface is severely incomplete for a job-related domain. While 'search_jobs' covers discovery, there are significant gaps such as creating, updating, or deleting job applications, managing profiles, or handling notifications, which are typical in job search workflows. This will likely cause agent failures when trying to perform full tasks.