341efd8c3d
CRITICAL FIX - Database Parameter (graphiti_core):
- Fixed graphiti_core/driver/neo4j_driver.py execute_query method
- database_ parameter was incorrectly added to params dict instead of kwargs
- Now correctly passed as keyword argument to Neo4j driver
- Impact: All queries now execute in configured database (not default 'neo4j')
- Root cause: Violated Neo4j Python driver API contract
Technical Details:
Previous code (BROKEN):
params.setdefault('database_', self._database) # Wrong - in params dict
result = await self.client.execute_query(cypher_query_, parameters_=params, **kwargs)
Fixed code (CORRECT):
kwargs.setdefault('database_', self._database) # Correct - in kwargs
result = await self.client.execute_query(cypher_query_, parameters_=params, **kwargs)
FIX - Index Creation Error Handling (MCP server):
- Added graceful handling for Neo4j IF NOT EXISTS bug
- Prevents MCP server crash when indices already exist
- Logs warning instead of failing initialization
- Handles EquivalentSchemaRuleAlreadyExists error gracefully
Files Modified:
- graphiti_core/driver/neo4j_driver.py (3 lines changed)
- mcp_server/src/graphiti_mcp_server.py (12 lines added error handling)
- mcp_server/pyproject.toml (version bump to 1.0.5)
Testing:
- Python syntax validation: PASSED
- Ruff formatting: PASSED
- Ruff linting: PASSED
Closes issues with:
- Data being stored in wrong Neo4j database
- MCP server crashing on startup with EquivalentSchemaRuleAlreadyExists
- NEO4J_DATABASE environment variable being ignored
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
127 lines
3.7 KiB
Markdown
127 lines
3.7 KiB
Markdown
# Docker Build Setup for Custom MCP Server
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## Overview
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This project uses GitHub Actions to automatically build a custom Docker image with MCP server changes and push it to Docker Hub. The image uses the **official graphiti-core from PyPI** (not local source).
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## Key Files
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### GitHub Actions Workflow
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- **File**: `.github/workflows/build-custom-mcp.yml`
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- **Triggers**:
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- Automatic: Push to `main` branch with changes to `graphiti_core/`, `mcp_server/`, or the workflow file
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- Manual: Workflow dispatch from Actions tab
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- **Builds**: Multi-platform image (AMD64 + ARM64)
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- **Pushes to**: `lvarming/graphiti-mcp` on Docker Hub
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### Dockerfile
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- **File**: `mcp_server/docker/Dockerfile.standalone` (official Dockerfile)
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- **NOT using custom Dockerfile** - we use the official one
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- **Pulls graphiti-core**: From PyPI (official version)
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- **Includes**: Custom MCP server code with added tools
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## Docker Hub Configuration
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### Required Secret
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- **Secret name**: `DOCKERHUB_TOKEN`
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- **Location**: GitHub repository → Settings → Secrets and variables → Actions
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- **Permissions**: Read & Write
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- **Username**: `lvarming`
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### Image Tags
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Each build creates multiple tags:
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- `lvarming/graphiti-mcp:latest`
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- `lvarming/graphiti-mcp:mcp-X.Y.Z` (MCP server version)
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- `lvarming/graphiti-mcp:mcp-X.Y.Z-core-A.B.C` (with graphiti-core version)
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- `lvarming/graphiti-mcp:sha-xxxxxxx` (git commit hash)
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## What's in the Custom Image
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✅ **Included**:
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- Official graphiti-core from PyPI (e.g., v0.23.0)
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- Custom MCP server code with:
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- `get_entities_by_type` tool
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- `compare_facts_over_time` tool
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- Other custom MCP tools in `mcp_server/src/graphiti_mcp_server.py`
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❌ **NOT Included**:
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- Local graphiti-core changes (we don't modify it)
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- Custom server/ changes (we don't modify it)
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## Build Process
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1. **Code pushed** to main branch on GitHub
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2. **Workflow triggers** automatically
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3. **Extracts versions** from pyproject.toml files
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4. **Builds image** using official `Dockerfile.standalone`
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- Context: `mcp_server/` directory
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- Uses graphiti-core from PyPI
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- Includes custom MCP server code
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5. **Pushes to Docker Hub** with multiple tags
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6. **Build summary** posted in GitHub Actions
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## Usage in Deployment
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### Unraid
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```yaml
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Repository: lvarming/graphiti-mcp:latest
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```
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### Docker Compose
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```yaml
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services:
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graphiti-mcp:
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image: lvarming/graphiti-mcp:latest
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# ... environment variables
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```
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### LibreChat Integration
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```yaml
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mcpServers:
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graphiti-memory:
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url: "http://graphiti-mcp:8000/mcp/"
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```
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## Important Constraints
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### DO NOT modify graphiti_core/
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- We use the official version from PyPI
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- Local changes break upstream compatibility
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- Causes Docker build issues
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- Makes merging with upstream difficult
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### DO modify mcp_server/
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- This is where custom tools live
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- Changes automatically included in next build
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- Push to main triggers new build
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## Monitoring Builds
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Check build status at:
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- https://github.com/Varming73/graphiti/actions
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- Look for "Build Custom MCP Server" workflow
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- Build takes ~5-10 minutes
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## Troubleshooting
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### Build Fails
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- Check Actions tab for error logs
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- Verify DOCKERHUB_TOKEN is valid
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- Ensure mcp_server code is valid
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### Image Not Available
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- Check Docker Hub: https://hub.docker.com/r/lvarming/graphiti-mcp
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- Verify build completed successfully
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- Check repository is public on Docker Hub
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### Wrong Version
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- Tags are based on pyproject.toml versions
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- Check `mcp_server/pyproject.toml` version
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- Check root `pyproject.toml` for graphiti-core version
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## Documentation
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Full guides available in `DOCS/`:
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- `GitHub-DockerHub-Setup.md` - Complete setup instructions
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- `Librechat.setup.md` - LibreChat + Unraid deployment
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- `README.md` - Navigation and overview
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