Hi,
I'm developing an AI agent using callin.io, incorporating tools that the agent can invoke to execute various tasks (like querying APIs, updating databases, etc.). I'm seeking the optimal strategy for organizing these tools:
- Should I develop all tools directly as nodes within the agent's workflow?
or - Should I utilize the
Call Workflow
node and structure each tool as an independent sub-workflow?
What are the advantages and disadvantages of each approach, particularly concerning performance, maintainability, and the transfer of context between tools?
Thanks in advance for any insights or suggestions!
I'm far from being a pro, but personally, I create a small workflow for each tool. Then you can reuse it with other agents if needed. More than that, you will be able to upgrade your tools if new nodes or services are developed.
Hello,
My personal approach is to begin with all tools integrated into a single workflow. This is the fastest method for launching an agent and ensures consistent context sharing across all components.
When specific tasks become reusable or begin consuming significant RAM, I then migrate them into separate sub-workflows and invoke them using the Execute Sub-workflow
node.
On callin.io Cloud, utilizing a sub-workflow does not incur additional execution costs; therefore, this decision is primarily driven by organizational structure and performance considerations.
For scenarios involving the combination of numerous distinct tasks, I recommend exploring the Model Context Protocol (MCP).
Links
- https://n8n.io/workflows/3770-build-your-own-n8n-workflows-mcp-server/
- MCP Client Tool node documentation | n8n Docs
This protocol enables you to expose each sub-workflow as a standard tool that the agent can discover dynamically.
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