solvro/ml-mcp

SOLVRO MCPWr

Knowledge Graph RAG System for PWr Intelligent assistant for Wrocław University of Science and Technology

Quick Start • Architecture • Features • Querying

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 backend-mcp (separate repo)   │            ml-mcp (this repo, no host ports)
┌─────────────┐   ┌──────────────┐│   ┌─────────────┐          ┌─────────────┐
│    nginx    │──▶│ chat-service │┼──▶│  MCP Server │─────────▶│    Neo4j    │
│   :8080     │   │              ││   │ :8005 (int.)│          │ :7687 (int.)│
└─────────────┘   └──────────────┘│   └─────────────┘          └─────────────┘
   auth + UI          agent       │ solvro-mcp-internal          mcp_network

• Intelligent Query Routing - Guardrails system determines query relevance
• Natural Language to Cypher - Converts questions to graph queries
• Knowledge Graph RAG - Retrieval-Augmented Generation with Neo4j
• MCP Protocol - Standard Model Context Protocol interface
• Observability - Optional Langfuse tracing integration
• Docker Ready - One command deployment

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Quick Start

# Setup
just setup
cp .env.example .env  # Edit with your API keys

# Run with Docker
just up      # Neo4j + MCP Server, reachable only by backend-mcp (no host ports)
just up-dev  # same, plus 127.0.0.1 ports for local work
just logs    # View logs
just down    # Stop services

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Architecture

System Overview

 backend-mcp (separate repo)   │            ml-mcp (this repo, no host ports)
┌─────────────┐   ┌──────────────┐│   ┌─────────────┐          ┌─────────────┐
│    nginx    │──▶│ chat-service │┼──▶│  MCP Server │─────────▶│    Neo4j    │
│   :8080     │   │              ││   │ :8005 (int.)│          │ :7687 (int.)│
└─────────────┘   └──────────────┘│   └─────────────┘          └─────────────┘
   auth + UI          agent       │ solvro-mcp-internal          mcp_network

The chat UI and the HTTP API that users talk to live in backend-mcp; this repository is the graph, the retrieval pipeline and the ETL that fills it.

Nothing is published on the host. just up-dev layers docker/compose.dev.yml on top, which republishes the ports on 127.0.0.1 for the Neo4j browser, just kg and uv run dump-graph.

RAG Pipeline

The heart of the system is a LangGraph-based RAG pipeline that intelligently processes user queries: