eddeda67b3
MCP Server Package Fixes: - Add build-system configuration to pyproject.toml - Fix module imports to use relative imports for proper packaging - Fix TypedDict import for Python 3.10 compatibility - Remove unsupported MCP SDK parameters (tags, meta) - Add GitHub Actions workflow for automatic PyPI publishing - Add PyPI publishing documentation and checklist Code Quality Improvements: - Fix code formatting in graphiti_core (line length, whitespace) This prepares v1.0.0 for publication to PyPI, enabling users to install with: uvx graphiti-mcp-varming 🤖 Generated with Claude Code (https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
126 lines
3.1 KiB
Markdown
126 lines
3.1 KiB
Markdown
# PyPI Publishing Setup Instructions
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This guide explains how to publish the `graphiti-mcp-varming` package to PyPI.
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## One-Time Setup
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### 1. Add PyPI Token to GitHub Secrets
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1. Go to your repository on GitHub: https://github.com/Varming73/graphiti
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2. Click **Settings** → **Secrets and variables** → **Actions**
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3. Click **New repository secret**
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4. Name: `PYPI_API_TOKEN`
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5. Value: Paste your PyPI API token (starts with `pypi-`)
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6. Click **Add secret**
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## Publishing a New Version
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### Option 1: Automatic Publishing (Recommended)
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1. Update the version in `mcp_server/pyproject.toml`:
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```toml
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version = "1.0.1" # Increment version
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```
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2. Commit the change:
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```bash
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cd mcp_server
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git add pyproject.toml
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git commit -m "Bump MCP server version to 1.0.1"
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git push
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```
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3. Create and push a tag:
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```bash
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git tag mcp-v1.0.1
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git push origin mcp-v1.0.1
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```
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4. GitHub Actions will automatically:
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- Build the package
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- Publish to PyPI
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- Create a GitHub release
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5. Monitor the workflow:
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- Go to **Actions** tab in GitHub
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- Watch the "Publish MCP Server to PyPI" workflow
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### Option 2: Manual Publishing
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If you prefer to publish manually:
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```bash
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cd mcp_server
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# Remove local graphiti-core override
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sed -i.bak '/\[tool\.uv\.sources\]/,/graphiti-core/d' pyproject.toml
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# Build the package
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uv build
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# Publish to PyPI
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uv publish --token your-pypi-token-here
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# Restore the backup if needed for local development
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mv pyproject.toml.bak pyproject.toml
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```
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## After Publishing
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Users can install your package with:
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```bash
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# Basic installation (Neo4j support included)
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uvx graphiti-mcp-varming
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# With FalkorDB support
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uvx --with graphiti-mcp-varming[falkordb] graphiti-mcp-varming
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# With all LLM providers (Anthropic, Groq, Gemini, Voyage, etc.)
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uvx --with graphiti-mcp-varming[providers] graphiti-mcp-varming
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# With everything
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uvx --with graphiti-mcp-varming[all] graphiti-mcp-varming
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```
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## Version Numbering
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Follow [Semantic Versioning](https://semver.org/):
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- **MAJOR** (1.0.0 → 2.0.0): Breaking changes
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- **MINOR** (1.0.0 → 1.1.0): New features, backwards compatible
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- **PATCH** (1.0.0 → 1.0.1): Bug fixes
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## Tag Naming Convention
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Use `mcp-v{VERSION}` format for tags:
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- `mcp-v1.0.0` - Initial release
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- `mcp-v1.0.1` - Patch release
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- `mcp-v1.1.0` - Minor release
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- `mcp-v2.0.0` - Major release
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This distinguishes MCP server releases from graphiti-core releases.
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## Troubleshooting
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### Publishing Fails with "File already exists"
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You tried to publish a version that already exists on PyPI. Increment the version number in `pyproject.toml` and try again.
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### "Invalid or missing authentication token"
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The PyPI token in GitHub secrets is incorrect or expired:
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1. Generate a new token at https://pypi.org/manage/account/token/
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2. Update the `PYPI_API_TOKEN` secret in GitHub
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### Workflow doesn't trigger
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Make sure:
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- Tag matches pattern `mcp-v*.*.*`
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- Tag is pushed to GitHub: `git push origin mcp-v1.0.0`
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- Workflow file is on the `main` branch
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## Checking Published Package
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After publishing, verify at:
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- PyPI page: https://pypi.org/project/graphiti-mcp-varming/
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- Test installation: `uvx graphiti-mcp-varming --help`
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