NeoCoder AI Workflow

Example Use Cases

• 1

  Follow standardized, Neo4j-guided development workflows (e.g., FIX, REFACTOR, DEPLOY) with mandatory testing and audit logging.

• 2

  Hybrid knowledge reasoning combining authoritative graph facts (Neo4j) with semantic context from a vector database (Qdrant) to answer complex queries with citations.

• 3

  Ingest and analyze research papers or large documents into a linked graph + vector store, build citation graphs, and perform provenance-preserving synthesis.

Description

NeoCoder is an MCP server implementation that combines Neo4j knowledge graphs, Qdrant vector databases, and LLM orchestration to create a hybrid Context-Augmented Reasoning system. It provides Neo4j-based workflow templates (FIX, REFACTOR, DEPLOY, KNOWLEDGE_QUERY, KNOWLEDGE_EXTRACT, etc.), mandatory verification steps, and full audit trails for workflow executions. The system supports multiple "incarnations" (coding, research, decision analysis, code analysis) and features dynamic knowledge extraction with provenance-preserving F-Contraction merging and citation-based synthesis.