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Merge pull request #13 from stefanoamorelli/tests/coverage
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‎.github/PULL_REQUEST_TEMPLATE.md‎

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# Pull Request
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## Description
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Brief description of changes made.
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## Type of Change
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- [ ] Bug fix (non-breaking change which fixes an issue)
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- [ ] New feature (non-breaking change which adds functionality)
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- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
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- [ ] Documentation update
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- [ ] Refactoring (no functional changes)
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## Testing
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- [ ] Tests pass locally (`pytest tests/`)
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- [ ] New tests added for new functionality
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- [ ] Manual testing completed
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## Checklist
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- [ ] Code follows project style guidelines
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- [ ] Self-review of code completed
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- [ ] Documentation updated (if applicable)
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- [ ] No breaking changes to existing functionality
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- [ ] Changes are backwards compatible
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## Additional Notes
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Any additional information about the changes.

‎.github/workflows/ci.yml‎

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name: CI
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on:
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push:
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branches: [ main ]
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pull_request:
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branches: [ main ]
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: ["3.13"]
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install uv
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uses: astral-sh/setup-uv@v3
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with:
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version: "latest"
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- name: Create virtual environment and install dependencies
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run: |
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uv venv
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uv pip install -e ".[test]"
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- name: Run tests
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run: |
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uv run pytest tests/ -v --tb=short
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- name: Test import functionality
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run: |
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uv run python -c "from nasdaq_data_link_mcp_os.server import mcp; print(f'Server name: {mcp.name}')"
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security:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout code
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uses: actions/checkout@v4
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- name: Run Trivy vulnerability scanner
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uses: aquasecurity/trivy-action@master
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with:
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scan-type: 'fs'
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scan-ref: '.'
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format: 'sarif'
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output: 'trivy-results.sarif'
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- name: Upload Trivy scan results to GitHub Security tab
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uses: github/codeql-action/upload-sarif@v3
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with:
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sarif_file: 'trivy-results.sarif'

‎.github/workflows/test.yml‎

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name: Tests
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on:
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push:
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branches: [ main, develop ]
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pull_request:
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branches: [ main ]
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jobs:
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test:
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runs-on: ubuntu-latest
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strategy:
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matrix:
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python-version: [3.13]
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install uv
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uses: astral-sh/setup-uv@v3
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with:
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version: "latest"
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- name: Install dependencies
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run: |
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uv sync --extra test
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- name: Run tests
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run: |
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uv run pytest tests/ -v --tb=short
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- name: Run tests with coverage
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run: |
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uv run pytest tests/ --cov=nasdaq_data_link_mcp_os --cov-report=xml --cov-report=term
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v3
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with:
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file: ./coverage.xml
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flags: unittests
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name: codecov-umbrella
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fail_ci_if_error: false
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lint:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: 3.13
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- name: Install uv
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uses: astral-sh/setup-uv@v3
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with:
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version: "latest"
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- name: Install dependencies
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run: |
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uv add --group dev ruff mypy
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- name: Run ruff (linter)
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run: |
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uv run ruff check nasdaq_data_link_mcp_os/ tests/
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- name: Run ruff (formatter)
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run: |
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uv run ruff format --check nasdaq_data_link_mcp_os/ tests/
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- name: Run mypy (type checker)
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run: |
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uv run mypy nasdaq_data_link_mcp_os/ --ignore-missing-imports
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continue-on-error: true # Don't fail CI on type errors initially

‎CONTRIBUTING.md‎

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# Contributing to Nasdaq Data Link MCP
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Thank you for your interest in contributing to the Nasdaq Data Link MCP Server! This document provides guidelines for contributing to the project.
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## Getting Started
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### Prerequisites
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- Python 3.13+
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- uv package manager
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- Git
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### Development Setup
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1. **Clone the repository**
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```bash
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git clone https://github.com/stefanoamorelli/nasdaq-data-link-mcp.git
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cd nasdaq-data-link-mcp
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```
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2. **Set up development environment**
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```bash
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uv init mcp
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uv add "mcp[cli]"
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uv add --group test "pytest>=7.0" "pytest-mock" "pytest-cov"
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```
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3. **Configure environment variables**
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```bash
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cp .env.example .env
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# Add your Nasdaq Data Link API key to .env
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```
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4. **Install the server in development mode**
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```bash
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uv run mcp install nasdaq_data_link_mcp_os/server.py --env-file .env --name "Nasdaq Data Link MCP Server" --with nasdaq-data-link --with pycountry
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```
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## Development Workflow
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### Code Style
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- Follow PEP 8 guidelines
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- Use meaningful variable names and clear function signatures
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- Add docstrings to all public functions and classes
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- Keep functions focused and single-purpose
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### Testing
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- Write tests for all new functionality
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- Run tests before submitting changes:
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```bash
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uv run pytest tests/
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```
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- Aim for good test coverage of critical functionality
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- Use mocking for external API calls in tests
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- All tests must pass in CI before merge
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### Code Quality
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- Run linting and formatting:
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```bash
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uv run ruff check nasdaq_data_link_mcp_os/ tests/
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uv run ruff format nasdaq_data_link_mcp_os/ tests/
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```
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- Run type checking:
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```bash
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uv run mypy nasdaq_data_link_mcp_os/
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```
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### Documentation
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- Update README.md if adding new features
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- Update relevant documentation in `docs/` directory
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- Include usage examples for new tools
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- Update the paper.md if changes affect the research description
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## Types of Contributions
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### Bug Reports
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When filing a bug report, please include:
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- Clear description of the issue
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- Steps to reproduce the problem
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- Expected vs actual behavior
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- Python version and environment details
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- Relevant error messages or logs
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### Feature Requests
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For new features, please:
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- Describe the use case and motivation
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- Explain how it fits with existing functionality
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- Consider backward compatibility
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- Provide examples of the desired behavior
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### Code Contributions
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#### Adding New Tools
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1. **Create the tool module** in the appropriate resource directory:
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```
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nasdaq_data_link_mcp_os/resources/[category]/[tool_name].py
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```
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2. **Follow the existing pattern**:
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- Import required dependencies
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- Define tool function with proper type hints
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- Add comprehensive error handling
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- Include docstring with usage examples
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3. **Register the tool** in `server.py`:
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```python
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@server.list_tools()
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async def list_tools() -> list[Tool]:
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return [
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# ... existing tools
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Tool(
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name="your_new_tool",
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description="Clear description of what the tool does",
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inputSchema={
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"type": "object",
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"properties": {
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# Define parameters
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}
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}
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)
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]
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```
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4. **Add tests** in `tests/test_tools.py` or create new test file
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#### Improving Existing Tools
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- Maintain backward compatibility
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- Update documentation and examples
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- Add tests for new functionality
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- Consider edge cases and error handling
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## Pull Request Process
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1. **Fork the repository** and create a feature branch:
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```bash
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git checkout -b feature/your-feature-name
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```
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2. **Make your changes** following the guidelines above
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3. **Test thoroughly**:
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```bash
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uv run pytest tests/
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```
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4. **Update documentation** as needed
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5. **Commit with clear messages**:
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```bash
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git commit -m "Add feature: description of what was added"
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```
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6. **Push to your fork** and create a pull request:
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```bash
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git push origin feature/your-feature-name
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```
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7. **Describe your changes** in the pull request:
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- What was changed and why
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- How to test the changes
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- Any breaking changes or special considerations
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## Code Review
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All contributions will be reviewed for:
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- Code quality and adherence to project standards
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- Test coverage and functionality
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- Documentation completeness
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- Backward compatibility
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- Security considerations
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## Community Guidelines
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- Be respectful and constructive in discussions
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- Help others learn and grow
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- Focus on the technical merits of contributions
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- Acknowledge the work of others
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## Getting Help
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- Check existing issues for similar problems
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- Ask questions in GitHub Discussions
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- Reach out to maintainers if needed
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## License
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By contributing to this project, you agree that your contributions will be licensed under the same MIT License that covers the project.
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## Recognition
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Contributors will be acknowledged in:
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- GitHub contributor list
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- Release notes for significant contributions
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- README.md for major features
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Thank you for helping make financial data more accessible through conversational AI!

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