alt Hacker NewsMy main complaint with mcp is that it doesn't compose well with other tools or code. Like if I want to pull 1000 jira tickets and do some custom analysis I can do that with cli or api just fine, but not mcp.
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Give the model a REPL and let it compose MCP calls either by using tool calls structured output, doing string processing or piping it to a fast cheap model to provide structured output.
This is the same as a CLI. Bash is nothing but a programming language and you can do the same approach by giving the model JavaScript and have it call MCP tools and compose them. If you do that you can even throw in composing it with CLis as well
You 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.
Right, that feels like something you'd do with a script and some API calls.
MCP is more for a back and forth communication between agent and app/service, or for providing tool/API awareness during other tasks. Like MCP for Jira would let the AI know it can grab tickets from Jira when needed while working on other things.
I guess it's more like: the MCP isn't for us - it's for the agent to decide when to use.