alt Hacker NewsYou can make it compose by also giving the agent the necessary tools to do so.
I encountered a similar scenario using Atlassian MCP recently, where someone needed to analyse hundreds of Confluence child pages from the last couple of years which all used the same starter template - I gave the agent a tool to let it call any other tool in batch and expose the results for subsequent tools to use as inputs, rather than dumping it straight into the context (e.g. another tool which gives each page to a sub-agent with a structured output schema and a prompt with extraction instructions, or piping the results into a code execution tool).
It turned what would have been hundreds of individual tool calls filling the context with multiple MBs of raw confluence pages, into a couple of calls returning relevant low-hundreds of KBs of JSON the agent could work further with.
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But in the context of this discussion, Atlassian has a CLI tool, acli. I'm not quite following why that wouldn't have worked here. As a normal CLI you have all the power you need over it, and the LLM could have used it to fetch all the relevant pages and save to disk, sample a couple to determine the regular format, and then write a script to extract out what they needed, right? Maybe I don't understand the use case you're describing.
Hmm, but you can't write a standard MCP (e.g. batch_tool_call) that calls other MCPs because the protocol doesn't give you a way to know what other MCPs are loaded in the runtime with you or any means to call them? Or have I got that wrong?
So I guess you had to modify the agent harness to do this? or I guess you could use... mcp-cli ... ??
The agent cannot compose MCPs.
What it can do is call multiple MCPs, dumping tons of crap into the context and then separately run some analysis on that data.
Composable MCPs would require some sort of external sandbox in which the agent can write small bits of code to transform and filter the results from one MCP to the next.