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This article details an architectural shift in multi-agent systems where Neo4j Aura Agents offload graph-specific computation from generic MCP connectors to native Cypher templates. By keeping data and compute together within the graph layer, this approach reduces the burden on general-purpose agents to interpret complex schema internals while maintaining clear separation between workflow logic and domain knowledge.
Grounding Salesforce Agentforce with Neo4j — multi-agent setup over MCP
In an earlier articles, we looked at multiple ways to ground Agentforce responses in a Neo4j knowledge graph. We focused both on different implementations (Apex actions, External Services, and MCP), as well as the overall agent architecture to correctly split… Read more →
In an earlier articles, we looked at multiple ways to ground Agentforce responses in a Neo4j knowledge graph. We focused both on different implementations (Apex actions, External Services, and MCP), as well as the overall agent architecture to correctly split the responsibilities between the data and reasoning based on the data. That way, we’ve got to the last installment: setting up agent without custom code, purely based on configuration. Move the question to the data, not the query plan to the generic agent. The moment we ponder the previous…
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