I am more interested in how MCP can change human interaction with software.
Practical example: there exists an MCP server for Jira.
Connect that MCP server to e.g. Claude and then you can write prompts like this:
"Produce a release notes document for project XYZ based on the Epics associated to version 1.2.3"
or
"Export to CSV all tickets with worklog related to project XYZ and version 1.2.3. Make sure the CSV includes these columns ....."
Especially the second example totally removes the need for the CSV export functionality in Jira. Now imagine a scenario in which your favourite AI is connected via MCP to different services. You can mix and match information from all of them.
Alibaba for example is making MCP servers for all of its user-facing services (alibaba mail, cloud drive, etc etc)
A chat UI powered by the appropriate MCP servers can provide a lot of value to regular end users and make it possible for people to use their own data easily in ways that earlier would require dedicated software solutions (exports, reports). People could use software for use cases that the original authors didn't even imagine.
It would, but the point of MCP is that it's discoverable by an AI. You can just go change it and it'll know how to use it immediately
If you go and change the parameters of a REST API, you need to modify every client that connects to it or they'll just plain not work. (Or you'll have a mess of legacy endpoints in your API)
Not a fan, I like the "give an LLM a virtual environment and let it code stuff" approach, but MCP is here to stay as far as I can see.
How does it remove the need for CSV export? The LLM can make mistakes right? Wouldn’t you want the LLM calling the deterministic csv export tool rather than trying to create a csv on its own?
Practical example: there exists an MCP server for Jira. Connect that MCP server to e.g. Claude and then you can write prompts like this:
"Produce a release notes document for project XYZ based on the Epics associated to version 1.2.3"
or
"Export to CSV all tickets with worklog related to project XYZ and version 1.2.3. Make sure the CSV includes these columns ....."
Especially the second example totally removes the need for the CSV export functionality in Jira. Now imagine a scenario in which your favourite AI is connected via MCP to different services. You can mix and match information from all of them.
Alibaba for example is making MCP servers for all of its user-facing services (alibaba mail, cloud drive, etc etc)
A chat UI powered by the appropriate MCP servers can provide a lot of value to regular end users and make it possible for people to use their own data easily in ways that earlier would require dedicated software solutions (exports, reports). People could use software for use cases that the original authors didn't even imagine.