graphiti
Verified Safeby Dhana009
Overview
A Micro-Agent Coordination Protocol (MCP) server for managing and querying a Neo4j-based knowledge graph, featuring LLM-powered entity/relationship extraction and semantic search.
Installation
uv run python D:/planning/FlowHUB-draft2/graphiti/graffiti_mcp_implementation/main.pyEnvironment Variables
- OPENAI_API_KEY
- OPENAI_LLM_MODEL
- OPENAI_EMBEDDING_MODEL
- OPENAI_EMBEDDING_DIMENSION
- OPENAI_ORGANIZATION
- NEO4J_URI
- NEO4J_USER
- NEO4J_PASSWORD
- NEO4J_DATABASE
Security Notes
The project demonstrates strong input validation via `src/validation.py` for all entity and relationship fields, significantly mitigating common injection risks. Neo4j queries use parameterized statements (`$param`), preventing Cypher injection. LLM output (JSON) is parsed and its structure is validated before further processing, avoiding direct code execution. The `OPENAI_API_KEY` is correctly handled as an environment variable, not hardcoded. Default Neo4j credentials are for a local development setup, not production. Potential risks largely stem from LLM vulnerabilities (e.g., advanced prompt injection) or misconfiguration in a production environment, rather than direct code-level flaws.
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