mcp-lightcast 0.2.1

MCP server for Lightcast API integration using FastMCP

MCP Lightcast Server

A production-ready Model Context Protocol (MCP) server that provides seamless integration with Lightcast APIs for job titles, skills analysis, and career data. Built with FastMCP and modern Python development practices.

🎯 Current Status: v0.2.1

🚀 Features

✅ Working APIs & Endpoints

🎯 Skills API (9/9 endpoints) - Version 9.33, 41,139 skills

• ✅ Skills Search - Search with filters (type, category, subcategory)
• ✅ Individual Skill Retrieval - Get detailed skill information by ID
• ✅ Skills Extraction from Text - Extract skills from job descriptions with confidence scores
• ✅ Bulk Skills Retrieval - Efficient batch processing of multiple skills
• ✅ Related Skills - Find skills related to a specific skill (POST endpoint working)
• ✅ Similar Skills - Find similar skills via Similarity API
• ✅ Skill Types - Get all available skill types
• ✅ Version Metadata - Complete API version and statistics information
• ✅ Skills Metadata - General skills taxonomy information

🏷️ Titles API (8/8 endpoints) - Version 5.47, 73,993 titles

• ✅ Job Title Search - Search Lightcast's comprehensive job title database
• ✅ Individual Title Retrieval - Get detailed title information by ID
• ✅ Bulk Title Retrieval - Efficient batch processing of multiple titles
• ✅ Title Normalization - Normalize raw job titles
• ✅ Title Hierarchy - Get hierarchical structure for titles
• ✅ Version Metadata - Complete API version and statistics information
• ✅ General Metadata - Latest version and attribution information
• ✅ Full Metadata - Comprehensive taxonomy information

🔄 Classification API (5/5 endpoints) - Version 2025.8

• ✅ Skills Extraction - Extract skills from text using classification models
• ✅ Available Versions - Get all available API versions
• ✅ Version Metadata - Detailed version information
• ✅ Skill Normalization - Normalize skill text via extraction
• ✅ Title Normalization - Normalize title text with fallback

🔗 Similarity API (7/7 endpoints) - Premium Features

• ✅ Available Models - Get all similarity models
• ✅ API Metadata - Similarity API capabilities
• ✅ Occupation Skills - Skills associated with occupations
• ✅ Similar Occupations - Find similar occupations
• ✅ Similar Skills - Find similar skills
• ✅ SOC Model - Direct SOC similarity queries
• ✅ Skill Model - Direct skill similarity queries

📊 Occupation Benchmark API (6/6 endpoints) - Premium Features

• ✅ API Metadata - Benchmark API capabilities
• ✅ Available Areas - Geographic areas available
• ✅ Available Metrics - All available benchmark metrics
• ✅ Benchmark Data - Salary and employment data
• ✅ SOC Dimension - SOC code dimension data
• ✅ LOT Dimension - LOT occupation dimension data

🛤️ Career Pathways API (3/3 endpoints) - Premium Features

• ✅ API Metadata - Career pathways capabilities
• ✅ Available Dimensions - Pathway analysis dimensions
• ✅ Pathway Analysis - Career transition analysis

💼 Job Postings API (3/3 endpoints) - Premium Features

• ✅ Available Facets - Job posting search facets
• ✅ Postings Summary - Job posting trends and statistics
• ✅ Top Skills - Most in-demand skills from job postings

🔄 Workflow Integration (2/2 endpoints) - Custom Workflows

• ✅ Title → Skills Workflow - Complete title normalization and skills extraction
• ✅ Simple Title Skills - Streamlined title-to-skills pipeline

🔧 **Core Functionality

• 🎯 Skills Extraction from Text - High accuracy skill identification from job descriptions
• 📊 Search & Discovery - Fast, filtered search across skills, titles, and job postings
• ⚡ Bulk Operations - Efficient processing of multiple items in single requests
• 🔄 Version Management - Uses "latest" keyword with backward compatibility
• 🔐 OAuth2 Authentication - Secure authentication with dynamic scope switching
• 🔗 Related & Similar Skills - Find skills relationships via multiple APIs
• 💼 Job Market Data - Real-time job posting analysis and trends
• 📊 Benchmarks & Analytics - Salary and employment data access
• 🛤️ Career Pathways - Career transition analysis and recommendations

🛠️ MCP Tools Available (23 core tools across 7 categories)

Skills Tools (7 tools)

API Docs: https://docs.lightcast.dev/apis/skills

• bulk_retrieve_skills - Efficient bulk skill retrieval
• extract_skills_from_text - Extract skills with custom confidence threshold
• find_similar_skills - Find similar skills via Similarity API
• get_skill_details - Get detailed skill information by ID
• get_skills_metadata - General skills taxonomy metadata
• get_related_skills - Find skills related to a specific skill (now working with POST endpoint)
• search_skills - Search skills with advanced filters (type, category, subcategory)

Titles Tools (4 tools)

API Docs: https://docs.lightcast.dev/apis/titles

• bulk_retrieve_titles - Efficient bulk title retrieval
• get_job_title_details - Get detailed title information by ID
• normalize_job_title - Normalize raw job titles
• search_job_titles - Search job titles in Lightcast database

Job Postings Tools (3 tools)

API Docs: https://docs.lightcast.dev/apis/job-postings

• get_job_posting_details - Get detailed job posting information
• get_posting_statistics - Job posting trends and analytics
• search_job_postings - Search real-time job market data

Classification Tools (1 tool)

API Docs: https://docs.lightcast.dev/apis/classification

• get_classification_metadata - Classification API capabilities and metadata

Occupation Benchmark Tools (2 tools)

API Docs: https://docs.lightcast.dev/apis/occupation-benchmark

• get_benchmark_metadata - Benchmark API capabilities and metadata
• get_occupation_benchmark - Salary and employment benchmarks by occupation

Similarity Tools (3 tools)

API Docs: https://docs.lightcast.dev/apis/similarity

• get_similarity_metadata - Similarity API capabilities and metadata
• get_pathways_metadata - Career pathways API capabilities and metadata

Unified Workflows (4 tools)

• analyze_job_posting_skills - Comprehensive job posting analysis
• normalize_title_and_get_skills - Complete title→skills workflow
• normalize_title_and_extract_skills - Alternative classification-based extraction

🛠️ Installation

Prerequisites

• Python 3.12+ (required for uv-dynamic-versioning)
• uv package manager (recommended) or pip
• Lightcast API credentials (Client ID and Secret with emsi_open scope). You can request free API access here which will give you access to the skills and titles taxonomies (subset of only the Skills and Titles APIs).

🚀 Quick Start with uvx (Recommended)

# Install and run directly from PyPI (no installation required)
uvx --from mcp-lightcast mcp-lightcast --help

# Run with environment variables
LIGHTCAST_CLIENT_ID=your_id LIGHTCAST_CLIENT_SECRET=your_secret \
uvx --from mcp-lightcast mcp-lightcast

# Use stdio transport for Claude Desktop
LIGHTCAST_CLIENT_ID=your_id LIGHTCAST_CLIENT_SECRET=your_secret \
uvx --from mcp-lightcast mcp-lightcast --transport stdio

📦 Install from PyPI

# Install globally
pip install mcp-lightcast

# Or with uv
uv tool install mcp-lightcast

# Run the server
mcp-lightcast --help

🔧 Development Installation

# 1. Clone the repository
git clone https://github.com/lawwu/mcp-lightcast.git
cd mcp-lightcast

# 2. Set up development environment 
make setup

# 3. Configure your API credentials
# Edit .env with your Lightcast API credentials

# 4. Validate configuration
make validate-config

# 5. Run the server
make run

🐳 Docker Installation

# Pull the latest image (when available)
docker pull ghcr.io/lawwu/mcp-lightcast:latest

# Run with environment variables
docker run --rm -it \
  -e LIGHTCAST_CLIENT_ID=your_id \
  -e LIGHTCAST_CLIENT_SECRET=your_secret \
  ghcr.io/lawwu/mcp-lightcast:latest

# Or with environment file
docker run --rm -it --env-file .env ghcr.io/lawwu/mcp-lightcast:latest

⚙️ Configuration

Environment Variables

Create a .env file with your Lightcast API credentials:

# Required - Lightcast API Configuration
LIGHTCAST_CLIENT_ID=your_client_id_here
LIGHTCAST_CLIENT_SECRET=your_client_secret_here

# Optional - API Configuration (with defaults)
LIGHTCAST_BASE_URL=https://api.lightcast.io
LIGHTCAST_OAUTH_URL=https://auth.emsicloud.com/connect/token
LIGHTCAST_OAUTH_SCOPE=emsi_open
LIGHTCAST_RATE_LIMIT=1000

# Optional - MCP Server Configuration
MCP_SERVER_NAME=lightcast-mcp-server
LOG_LEVEL=INFO
MASK_ERROR_DETAILS=true

Lightcast API Access

To use this server, you need:

1. 📝 A Lightcast API account
2. 🔑 Client ID and Client Secret for OAuth2 authentication
3. 🎯 Access to the following Lightcast APIs:
   • Titles API - Job title search and normalization
   • Skills API - Skills search and categorization
   • Classification API - Occupation code mapping
   • Similarity API - Skills and occupation relationships

🎯 Usage

Command Line Interface

The server includes a comprehensive CLI with multiple options:

# Basic usage (uses streamable-http on port 3000 by default)
mcp-lightcast

# Use stdio transport (for Claude Desktop integration)
mcp-lightcast --transport stdio

# Use streamable-http transport with custom port
mcp-lightcast --transport streamable-http --port 8080

# With custom log level
mcp-lightcast --log-level DEBUG

# Validate configuration without starting server
mcp-lightcast --validate-config

# Use custom environment file
mcp-lightcast --env-file /path/to/custom.env

# Quiet mode (no logging)
mcp-lightcast --quiet

# Show help
mcp-lightcast --help

Development Commands

Using the included Makefile for easy development:

# Quick development setup and run
make dev

# Run with debug logging
make dev-server

# Run all quality checks
make check

# Run tests with coverage
make test-coverage

# Show Claude Desktop configuration
make claude-config

Claude Desktop Integration

Using uv (Recommended)

{
  "mcpServers": {
    "lightcast": {
      "command": "uv",
      "args": [
        "run",
        "--directory",
        "/path/to/mcp-lightcast",
        "mcp-lightcast"
      ],
      "env": {
        "LIGHTCAST_CLIENT_ID": "your_client_id",
        "LIGHTCAST_CLIENT_SECRET": "your_client_secret"
      }
    }
  }
}

Using Docker

{
  "mcpServers": {
    "lightcast": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e", "LIGHTCAST_CLIENT_ID",
        "-e", "LIGHTCAST_CLIENT_SECRET",
        "ghcr.io/lawwu/mcp-lightcast:latest"
      ],
      "env": {
        "LIGHTCAST_CLIENT_ID": "your_client_id",
        "LIGHTCAST_CLIENT_SECRET": "your_client_secret"
      }
    }
  }
}

Using uvx (Isolated)

{
  "mcpServers": {
    "lightcast": {
      "command": "uvx",
      "args": [
        "--from",
        "mcp-lightcast",
        "mcp-lightcast"
      ],
      "env": {
        "LIGHTCAST_CLIENT_ID": "your_client_id",
        "LIGHTCAST_CLIENT_SECRET": "your_client_secret"
      }
    }
  }
}

🔧 Detailed Tool Usage Examples

🎯 Skills Tools

search_skills - Search skills with advanced filters

skills = await search_skills(
    query="python programming",
    limit=10,
    skill_type="Hard Skill",  # Optional: filter by skill type
    category="Information Technology",  # Optional: filter by category
    version="latest"  # Uses latest API version
)

extract_skills_from_text - Extract skills from job descriptions

# Extract skills with custom confidence threshold
skills = await extract_skills_from_text(
    text="Looking for Python developer with React and database experience...",
    confidence_threshold=0.7,
    version="latest"
)

extract_skills_simple - Extract skills with default settings

# Quick skills extraction with default confidence (0.5)
skills = await extract_skills_simple(
    text="We need Java developers with Spring Boot experience",
    version="latest"
)

bulk_retrieve_skills - Efficient bulk skill retrieval

# Get multiple skills in one request
skills = await bulk_retrieve_skills(
    skill_ids=["KS125LS6N7WP4S6SFTCK", "KS440C66FGP5WGWYMP0F"],
    version="latest"
)

🏷️ Titles Tools

search_job_titles - Search job titles

titles = await search_job_titles(
    query="software engineer",
    limit=10,
    version="latest"
)

get_job_title_details - Get detailed title information

title = await get_job_title_details(
    title_id="ET6850661D6AE5FA86",
    version="latest"
)

bulk_retrieve_titles - Efficient bulk title retrieval

titles = await bulk_retrieve_titles(
    title_ids=["ET6850661D6AE5FA86", "ETBF8AE9187B3810C5"],
    version="latest"
)

📊 Metadata Tools

get_skills_version_metadata - API version information

metadata = await get_skills_version_metadata(version="latest")
# Returns: version, skill_count, language_support, skill_types, etc.

get_titles_version_metadata - API version information

metadata = await get_titles_version_metadata(version="latest")
# Returns: version, title_count, removed_title_count, fields

⚠️ Limited Availability Tools

Some tools require premium authentication scopes or have endpoint limitations:

normalize_job_title - ❌ Requires premium scope

# Currently returns 401 Unauthorized with emsi_open scope
result = await normalize_job_title("sr software dev")

analyze_job_posting_skills - ✅ Working via skills extraction

# Uses skills extraction instead of normalization
result = await analyze_job_posting_skills(
    job_title="Software Engineer",
    job_description="Full job description text...",
    extract_from_description=True  # Uses working skills extraction
)

🎯 Example Workflows

1. Extract Skills from Job Description

# Analyze a job posting to extract relevant skills
job_description = """
We're looking for a Senior Software Engineer with expertise in Python, 
React, and cloud technologies. Experience with Docker, Kubernetes, 
and AWS is required. Strong communication skills and team collaboration 
abilities are essential.
"""

# Extract skills with high confidence
skills = await extract_skills_from_text(
    text=job_description,
    confidence_threshold=0.8,
    version="latest"
)

print(f"High-confidence skills found: {len(skills)}")
for skill in skills:
    print(f"- {skill['name']} (confidence: {skill['confidence']:.2f})")

2. Compare Skills Across Job Titles

# Search and compare skills requirements for different roles
titles = ["Data Scientist", "Machine Learning Engineer", "Software Engineer"]
title_skills = {}

for title in titles:
    # Search for the title
    title_results = await search_job_titles(query=title, limit=1)
    if title_results:
        title_id = title_results[0]['id']
        
        # Get detailed title information  
        title_details = await get_job_title_details(title_id)
        title_skills[title] = title_details
        
print("Job title comparison completed")

3. Bulk Skills Analysis

# Efficiently analyze multiple skills at once
skill_names = ["Python", "JavaScript", "Machine Learning", "Docker"]

# First search for skill IDs
skill_ids = []
for name in skill_names:
    results = await search_skills(query=name, limit=1)
    if results:
        skill_ids.append(results[0]['id'])

# Get detailed information for all skills in one request
if skill_ids:
    detailed_skills = await bulk_retrieve_skills(skill_ids)
    
    for skill in detailed_skills:
        print(f"Skill: {skill['name']}")
        print(f"Type: {skill.get('type', {}).get('name', 'Unknown')}")
        print(f"Category: {skill.get('category', 'Unknown')}")
        print("---")

4. API Version and Statistics

# Get comprehensive API information
skills_meta = await get_skills_version_metadata()
titles_meta = await get_titles_version_metadata()

print(f"Skills API v{skills_meta['version']}: {skills_meta['skill_count']:,} skills")
print(f"Languages: {', '.join(skills_meta['language_support'])}")
print(f"Skill types: {len(skills_meta['skill_types'])}")

print(f"Titles API v{titles_meta['version']}: {titles_meta['title_count']:,} titles")

🧪 Development

Prerequisites

• Python 3.12+ (required)
• uv package manager
• Docker (for containerized development)
• Make (for development commands)

Development Setup

# Clone and setup
git clone https://github.com/lawwu/mcp-lightcast.git
cd mcp-lightcast

# Quick setup (installs dependencies, creates .env)
make setup

# Install development dependencies only  
make install-dev

# Run development server with debug logging
make dev-server

Project Structure

mcp-lightcast/
├── 📁 src/mcp_lightcast/           # Main package
│   ├── __init__.py                 # CLI entry point with Click
│   ├── __main__.py                 # Module execution entry
│   ├── server.py                   # FastMCP server instance
│   ├── 📁 auth/                    # Authentication modules
│   │   ├── __init__.py
│   │   └── oauth.py               # OAuth2 implementation
│   ├── 📁 apis/                    # API client modules  
│   │   ├── __init__.py
│   │   ├── base.py                # Base client with error handling
│   │   ├── titles.py              # Titles API client
│   │   ├── skills.py              # Skills API client
│   │   ├── classification.py      # Classification API client
│   │   └── similarity.py          # Similarity API client
│   ├── 📁 tools/                   # MCP tools registration
│   │   ├── __init__.py
│   │   ├── titles_tools.py        # Title-related MCP tools
│   │   ├── skills_tools.py        # Skills-related MCP tools
│   │   ├── workflow_tools.py      # Combined workflow tools
│   │   └── normalize_title_get_skills.py  # Core workflow logic
│   └── 📁 utils/                   # Utility functions
│       └── __init__.py
├── 📁 tests/                       # Test suite
│   ├── 📁 unit/                    # Unit tests
│   ├── 📁 integration/             # Integration tests
│   └── conftest.py                # Pytest fixtures
├── 📁 config/                      # Configuration management
│   └── settings.py                # Pydantic settings
├── 📁 .github/workflows/           # CI/CD pipelines
│   └── ci.yml                     # GitHub Actions workflow
├── 🐳 Dockerfile                   # Production container
├── 🐳 Dockerfile.dev               # Development container  
├── 🐳 docker-compose.yml           # Multi-service setup
├── 📋 Makefile                     # Development commands
├── 📦 pyproject.toml               # Project metadata & dependencies
├── 🔒 uv.lock                      # Dependency lock file
└── 📖 README.md                    # This file

Development Workflow

Code Quality & Testing

# Run all quality checks (lint + type-check + test)
make check

# Individual quality checks
make lint           # Ruff linting
make type-check     # MyPy type checking  
make format         # Black + Ruff formatting

# Testing options
make test           # Run all tests
make test-coverage  # Tests with coverage report
make test-basic     # Basic functionality test

Docker Development

# Build Docker images
make docker-build       # Production image
make docker-build-dev   # Development image

# Run with Docker
make docker-run         # Run production container
make docker-dev         # Run development container

# Test Docker configuration
make docker-test        # Validate container setup

uv Package Management

# Dependency management
make uv-lock           # Generate lockfile
make uv-sync           # Sync from lockfile
make uv-update         # Update all dependencies

# Add dependencies
make uv-add PACKAGE=requests
make uv-add-dev PACKAGE=pytest-mock

API Reference

Rate Limits

• Default: 1000 requests per hour per API key
• Rate limit headers are included in responses
• Rate limit errors (429) are handled gracefully

Error Handling

• Authentication errors are automatically retried
• Rate limits include reset time information
• API errors include detailed status codes and messages
• Network errors are handled with appropriate timeouts

API Version Flexibility

The MCP server provides flexible version management:

• Default: "latest" - Always uses the newest available API version
• Backward Compatible: Users can specify any previous version (e.g., "5.47", "9.33")
• Future-Proof: Automatically gets new API features when Lightcast releases updates

Examples:

# Use latest version (default)
search_job_titles("software engineer")

# Use specific version for consistency
search_job_titles("software engineer", version="5.47")

# Use older version if needed
search_skills("python", version="9.32")

Current API Versions:

• Skills API: 9.33 with 41,139 skills (English, Spanish, French support)
• Titles API: 5.47 with 73,993 titles
• Both APIs use "latest" keyword for automatic version management

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

📚 Documentation & Support

API Documentation

• Lightcast API Documentation - Official Lightcast API reference
• FastMCP Documentation - FastMCP framework documentation
• Model Context Protocol - MCP specification

Project Resources

• PyPI Package - Official Python package
• GitHub Repository - Source code and issues
• GitHub Releases - Version history and changelog

Getting Help

• Issues: GitHub Issues for bugs and feature requests
• Discussions: GitHub Discussions for questions and community support
• Lightcast Support: Contact Lightcast for API access and credentials

Current Status

• Version: 0.2.0 (Production Ready)
• API Coverage: 43/43 endpoints (100%)
• MCP Tools: 23 core tools (streamlined)
• Premium Features: All working with user credentials
• Python: 3.12+ required
• License: MIT