UpworkBridge
Enables AI agents to search Upwork jobs across skill categories with smart scoring, generate tailored proposals using freelancer profile data, and manage contracts and messages through Upwork's API.
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., "@UpworkBridgesearch for AI/ML implementation jobs"
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.
UpworkBridge — MCP Server for Upwork
A Model Context Protocol (MCP) server that connects AI coding assistants and agentic workflows to the Upwork freelance marketplace. Enables AI-powered job discovery, proposal generation, and contract management through a structured tool interface.
Overview
UpworkBridge exposes Upwork's platform capabilities as MCP tools, allowing AI agents to:
Search jobs across 25+ skill categories with configurable scoring and filtering
Generate tailored proposals using freelancer profile data and job-specific context
Manage contracts and messages (proposed — requires OAuth scope)
Monitor activity via a cron-enabled scanning pipeline
Related MCP server: upwork-mcp
Architecture
┌─────────────────────────────────────────────────────┐
│ AI Assistant (Host) │
│ (Claude Code, Cursor, Copilot, Hermes Agent, etc.) │
└────────────────────┬────────────────────────────────┘
│ MCP Protocol (stdio/SSE)
▼
┌─────────────────────────────────────────────────────┐
│ UpworkBridge Server │
│ │
│ ┌──────────────┐ ┌───────────────────────────┐ │
│ │ Scanner │ → │ Job Search & Scoring │ │
│ │ Module │ │ - 25+ predefined queries │ │
│ └──────────────┘ │ - Multi-tier categories │ │
│ │ - Smart scoring engine │ │
│ ┌──────────────┐ └───────────────────────────┘ │
│ │ Proposer │ ┌───────────────────────────┐ │
│ │ Module │ → │ Proposal Generation │ │
│ └──────────────┘ │ - AI-assisted drafting │ │
│ │ - Skill-based templates │ │
│ │ - Best practices engine │ │
│ ┌──────────────┐ └───────────────────────────┘ │
│ │ OAuth │ ┌───────────────────────────┐ │
│ │ Handler │ → │ Token Management │ │
│ └──────────────┘ │ - OAuth 2.0 auth flow │ │
│ │ - Auto token refresh │ │
│ ┌──────────────┐ └───────────────────────────┘ │
│ │ Config │ ┌───────────────────────────┐ │
│ │ Engine │ → │ Search params, scoring │ │
│ └──────────────┘ │ weights, user profile │ │
│ └───────────────────────────┘ │
└────────────────────┬────────────────────────────────┘
│ Upwork API (OAuth 2.0)
▼
┌─────────────────────────────────────────────────────┐
│ Upwork Platform │
│ Job listings · Proposals · Contracts · Messages │
└─────────────────────────────────────────────────────┘Quick Start
Prerequisites
Python 3.10+
Upwork API credentials (OAuth 2.0 — apply here)
Installation
# Clone the repo
git clone https://github.com/your-org/upworkbridge.git
cd upworkbridge
# Install dependencies
pip install -r requirements.txt
# Configure credentials
cp config.example.py config.py
# Edit config.py with your Upwork Client ID and Secret
# Run initial OAuth authorization
python src/scanner.py --auth
# Search for jobs
python src/scanner.py
# Generate a proposal
python src/propose.py --job-id <JOB_ID>MCP Integration
To connect UpworkBridge to an MCP-compatible AI assistant:
{
"mcpServers": {
"upwork": {
"command": "python",
"args": ["/path/to/upworkbridge/src/scanner.py", "--mcp"],
"env": {
"UPWORK_CLIENT_ID": "your_client_id",
"UPWORK_CLIENT_SECRET": "your_client_secret"
}
}
}
}Features
🔍 Job Scanner
Searches Upwork across 10 categories organized in 3 tiers:
Tier | Category | Target Rate | Query Volume |
1 | AI/ML Implementation | $85–$175/hr | 5 queries |
1 | Government/Defense IT | $100–$250/hr | 2 queries |
2 | Data Analysis | $40–$80/hr | 3 queries |
2 | Process Automation | $50–$100/hr | 3 queries |
2 | Technical Writing | $40–$80/hr | 2 queries |
3 | Language Services | $35–$55/hr | 2 queries |
3 | Systems Admin | $35–$65/hr | 2 queries |
3 | Virtual Assistant | $20–$45/hr | 1 query |
3 | Real Estate | $30–$60/hr | 1 query |
3 | AI Training | $40–$80/hr | 1 query |
📊 Smart Scoring
Jobs are scored 0–100 based on:
Factor | Weight | Description |
Payment Verified | 25 pts | Client must have verified payment |
Client Rating | 10× | Multiplied by (rating - 3) / 2 |
Budget | 5–30 pts | Scaled by project value |
Region | 10 pts | US/CA/UK/AU preference |
Freshness | 15 pts | Posted within 24 hours |
Competition | 5–10 pts | Fewer proposals = higher score |
📝 Proposal Generator
AI-assisted proposal drafting with:
Job-specific context analysis
Freelancer profile integration
Skill-based template matching
Best-practices checklist
Dry-run mode for review before submission
Configuration
All configuration lives in config.py:
API Credentials — OAuth 2.0 client ID and secret
Search Queries — Customizable per category
Scoring Weights — Adjustable preference factors
Filtering Rules — Minimum client rating, budget thresholds, country preferences
Freelancer Profile — Skills, certifications, portfolio, rate range
Roadmap
Job scanning with multi-query search
AI-assisted proposal generation
OAuth 2.0 token management
MCP server mode (stdio transport)
Proposal submission & tracking
Message monitoring
Contract status tracking
Docker deployment
Pre-built GitHub Action for cron scanning
License
MIT — see LICENSE.
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Maintenance
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