Lars Varming 341efd8c3d Fix: Critical database parameter bug + index creation error handling

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>

2025-11-10 11:37:16 +01:00

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Graphiti Project Overview

⚠️ CRITICAL CONSTRAINT: Fork-Specific Rules

DO NOT MODIFY graphiti_core/ DIRECTORY

This is a fork that maintains custom MCP server changes while using the official graphiti-core from PyPI.

Allowed modifications:

✅ mcp_server/ - Custom MCP server implementation
✅ DOCS/ - Documentation
✅ .github/workflows/build-custom-mcp.yml - Build workflow

Forbidden modifications:

❌ graphiti_core/ - Use official PyPI version
❌ server/ - Use upstream version
❌ Root pyproject.toml (unless critical for build)

Why this matters:

Docker builds use graphiti-core from PyPI, not local source
Local changes break upstream compatibility
Causes merge conflicts when syncing upstream
Custom image only includes MCP server changes

Purpose

Graphiti is a Python framework for building and querying temporally-aware knowledge graphs, specifically designed for AI agents operating in dynamic environments. It continuously integrates user interactions, structured/unstructured data, and external information into a coherent, queryable graph with incremental updates and efficient retrieval.

Key Features

Bi-temporal data model: Explicit tracking of event occurrence times
Hybrid retrieval: Combining semantic embeddings, keyword search (BM25), and graph traversal
Custom entity definitions: Support via Pydantic models
Real-time incremental updates: No batch recomputation required
Multiple graph backends: Neo4j and FalkorDB support
Optional OpenTelemetry tracing: For distributed systems

Use Cases

Integrate and maintain dynamic user interactions and business data
Facilitate state-based reasoning and task automation for agents
Query complex, evolving data with semantic, keyword, and graph-based search methods

Relationship to Zep

Graphiti powers the core of Zep, a turn-key context engineering platform for AI Agents. This is the open-source version that provides flexibility for custom implementations.

Tech Stack

Language: Python 3.10+
Package Manager: uv (modern, fast Python package installer)
Core Dependencies:
- Pydantic 2.11.5+ (data validation and models)
- Neo4j 5.26.0+ (primary graph database)
- OpenAI 1.91.0+ (LLM inference and embeddings)
- Tenacity 9.0.0+ (retry logic)
- DiskCache 5.6.3+ (caching)
Optional Integrations:
- Anthropic (Claude models)
- Google Gemini
- Groq
- FalkorDB (alternative graph database)
- Kuzu (graph database)
- Neptune (AWS graph database)
- VoyageAI (embeddings)
- Sentence Transformers (local embeddings)
- OpenTelemetry (tracing)
Development Tools:
- Ruff (linting and formatting)
- Pyright (type checking)
- Pytest (testing framework with pytest-asyncio and pytest-xdist)

Project Version

Current version: 0.23.0 (latest upstream) Fork MCP Server version: 1.0.0

Repositories

Upstream: https://github.com/getzep/graphiti
This Fork: https://github.com/Varming73/graphiti

Custom Docker Image

Docker Hub: lvarming/graphiti-mcp
Automated builds: Via GitHub Actions
Contains: Official graphiti-core + custom MCP server
See: docker_build_setup memory for details

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