Interoperable Graph Context: Memgraph MCP Client — Connect, Fetch, and Orchestrate Across MCP Servers

Connecting LLMs to other enterprise tools usually means writing custom adapters for every API. It doesn’t scale. MCP fixes that by giving AI tools a shared standard for discovery, connection, and orchestration.

In this session we break down why MCP matters, what the Memgraph MCP Server exposes to agents, and how the new Memgraph MCP Client in Memgraph Lab connects to multiple MCP servers at once. You’ll see a live end-to-end workflow where a single agent runs graph queries, generates charts, and pulls external context. All this will be done through MCP, without any custom wiring required.

What You’ll See

• The “Why MCP” story
• What the Memgraph MCP Server exposes
• How Memgraph Lab functions as an MCP Client
• Live demo of running cross-system workflows inside one agent flow

What You’ll Learn

• How MCP removes custom code from agent workflows
• How to design composable multi-server workflows without overwhelming the LLM
• Guardrails and observability considerations when coordinating multiple MCP tools
• Patterns for scaling agentic systems that blend graph context with external APIs cleanly