3c25268afc
- Reorganized MCP server into clean, scalable directory structure: - `src/config/` - Configuration modules (schema, managers, provider configs) - `src/services/` - Services (queue, factories) - `src/models/` - Data models (entities, responses) - `src/utils/` - Utilities (formatting, helpers) - `tests/` - All test files - `config/` - Configuration files (YAML, examples) - `docker/` - Docker setup files - `docs/` - Documentation - Added `main.py` wrapper for seamless transition - Maintains existing command-line interface - All deployment scripts continue to work unchanged - **Queue Service Interface Fix**: Fixed missing `add_episode()` and `initialize()` methods - Server calls at `graphiti_mcp_server.py:276` and `:755` now work correctly - Eliminates runtime crashes on startup and episode processing - Updated imports throughout restructured codebase - Fixed Python module name conflicts (renamed `types/` to `models/`) - **MCP Server Tests Action** (`.github/workflows/mcp-server-tests.yml`) - Runs on PRs targeting main with `mcp_server/**` changes - Configuration validation, syntax checking, unit tests - Import structure validation, dependency verification - Main.py wrapper functionality testing - **MCP Server Lint Action** (`.github/workflows/mcp-server-lint.yml`) - Code formatting with ruff (100 char line length, single quotes) - Comprehensive linting with GitHub-formatted output - Type checking with pyright (baseline approach for existing errors) - Import sorting validation - Added ruff and pyright configuration to `mcp_server/pyproject.toml` - Proper tool configuration for the new structure - Enhanced development dependencies with formatting/linting tools - All existing tests moved and updated for new structure - Import paths updated throughout test suite - Validation scripts enhanced for restructured codebase - **Improved Maintainability**: Clear separation of concerns - **Better Scalability**: Organized structure supports growth - **Enhanced Developer Experience**: Proper linting, formatting, type checking - **Automated Quality Gates**: CI/CD ensures code quality on every PR - **Zero Breaking Changes**: Maintains full backwards compatibility 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
2.4 KiB
2.4 KiB
Instructions for Using Graphiti's MCP Tools for Agent Memory
Before Starting Any Task
- Always search first: Use the
search_nodestool to look for relevant preferences and procedures before beginning work. - Search for facts too: Use the
search_factstool to discover relationships and factual information that may be relevant to your task. - Filter by entity type: Specify
Preference,Procedure, orRequirementin your node search to get targeted results. - Review all matches: Carefully examine any preferences, procedures, or facts that match your current task.
Always Save New or Updated Information
- Capture requirements and preferences immediately: When a user expresses a requirement or preference, use
add_memoryto store it right away.- Best practice: Split very long requirements into shorter, logical chunks.
- Be explicit if something is an update to existing knowledge. Only add what's changed or new to the graph.
- Document procedures clearly: When you discover how a user wants things done, record it as a procedure.
- Record factual relationships: When you learn about connections between entities, store these as facts.
- Be specific with categories: Label preferences and procedures with clear categories for better retrieval later.
During Your Work
- Respect discovered preferences: Align your work with any preferences you've found.
- Follow procedures exactly: If you find a procedure for your current task, follow it step by step.
- Apply relevant facts: Use factual information to inform your decisions and recommendations.
- Stay consistent: Maintain consistency with previously identified preferences, procedures, and facts.
Best Practices
- Search before suggesting: Always check if there's established knowledge before making recommendations.
- Combine node and fact searches: For complex tasks, search both nodes and facts to build a complete picture.
- Use
center_node_uuid: When exploring related information, center your search around a specific node. - Prioritize specific matches: More specific information takes precedence over general information.
- Be proactive: If you notice patterns in user behavior, consider storing them as preferences or procedures.
Remember: The knowledge graph is your memory. Use it consistently to provide personalized assistance that respects the user's established preferences, procedures, and factual context.