NeoCoder: Neo4j-Guided AI Coding Workflow

Name: NeoCoder: Neo4j-Guided AI Coding Workflow
Author: angrysky56

@angrysky56

NeoCoder: Neo4j-Guided AI Coding Workflow について

An MCP server allowing AI assistants to use a Neo4j knowledge graph as their primary, dynamic instruction manual and long term project memory with adaptive templating and autonomous tool development tools.

#neo4j #coder #claude #llm #mcp-server #vibe-coding

基本情報

カテゴリ

推論

ライセンス

MIT

ランタイム

python

トランスポート

stdio

公開者

angrysky56

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "NeoCoder-neo4j-ai-workflow": {
      "command": "uv",
      "args": [
        "venv"
      ]
    }
  }
}

ツール

Verify Neo4j connection status

Entry point for AI navigation

Get a specific workflow template

See all available templates

View coding standards

View project details including README

List all projects in the system

Record a successful workflow completion

View audit trail of work done

Provide feedback on templates

Run direct Cypher queries

Execute write operations on the graph

概要

What is NeoCoder: Neo4j-Guided AI Coding Workflow?

An MCP server that enables AI assistants like Claude to use a Neo4j knowledge graph and Qdrant vector database as a dynamic instruction manual and project memory for standardized coding workflows and hybrid reasoning.

How to use NeoCoder: Neo4j-Guided AI Coding Workflow?

Install prerequisites (Neo4j, Qdrant, Python 3.10+, uv, Claude Desktop), clone the repository, set up a virtual environment, install dependencies, start Neo4j and Qdrant, then configure Claude Desktop with the provided JSON config. Use the suggested system prompt to guide interactions. Monitor server health with get_cleanup_status() and check_connection() tools.

Key features of NeoCoder: Neo4j-Guided AI Coding Workflow

Hybrid knowledge reasoning combining Neo4j graphs and Qdrant vectors
Dynamic knowledge extraction from documents, code, and conversations
Citation-based analysis with full source attribution
Multi-incarnation system for coding, research, and decision support
Intelligent workflow templates with mandatory verification steps
Production-ready process management with automatic cleanup and signal handling

Use cases of NeoCoder: Neo4j-Guided AI Coding Workflow

Guided software development tasks using Neo4j-defined action templates
Research paper analysis with citation graphs and semantic content
Knowledge management with dynamic synthesis and structured storage
Decision support using context-augmented reasoning from multiple databases

FAQ from NeoCoder: Neo4j-Guided AI Coding Workflow

What are the runtime dependencies?

Neo4j (local or remote), Qdrant (Docker recommended), Python 3.10+, uv, and Claude Desktop. Optional tools include WolframAlpha and AST MCP servers.

How do I configure Neo4j connection?

Set environment variables NEO4J_URL, NEO4J_USERNAME, NEO4J_PASSWORD, and NEO4J_DATABASE (defaults: bolt://localhost:7687, neo4j, neo4j, neo4j). The password must match your Neo4j database password.

How do I start Qdrant?

Run docker run -p 6333:6333 -p 6334:6334 -v "$(pwd)/qdrant_storage:/qdrant/storage:z" qdrant/qdrant for persistent storage.

Is the server production-ready?

Yes, it includes signal handlers, resource tracking, zombie cleanup, memory management, and background task management to prevent process leaks.

What transport does the MCP server use?

It uses stdio transport as configured via MCP_TRANSPORT=1 in the environment.

「推論」の他のコンテンツ

Agentic Tools MCP Server

Pimzino

A comprehensive Model Context Protocol (MCP) server providing AI assistants with powerful task management and agent memories capabilities with project-specific storage.