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Cool, adding this to my list of MCP CLIs:

  - https://github.com/apify/mcpc
  - https://github.com/chrishayuk/mcp-cli
  - https://github.com/wong2/mcp-cli
  - https://github.com/f/mcptools
  - https://github.com/adhikasp/mcp-client-cli
  - https://github.com/thellimist/clihub
  - https://github.com/EstebanForge/mcp-cli-ent
  - https://github.com/knowsuchagency/mcp2cli
  - https://github.com/philschmid/mcp-cli
  - https://github.com/steipete/mcporter
  - https://github.com/mattzcarey/cloudflare-mcp
  - https://github.com/assimelha/cmcp

This looks useful.

One pattern we've been seeing internally is that once teams standardize API interactions through a single interface (or agent layer), debugging becomes both easier and harder.

Easier because there's a central abstraction, harder because failures become more opaque.

In production incidents we often end up tracing through multiple abstraction layers before finding the real root cause.

Curious if you've built anything into the CLI to help with observability or tracing when something fails.

We had `curl`, HTTP and OpenAPI specs, but we created MCP. Now we're wrapping MCP into CLIs...

Tokens saved should not be your north star metric. You should be able to show that tool call performance is maintained while consuming fewer tokens. I have no idea whether that is the case here.

As an aside: this is a cool idea but the prose in the readme and the above post seem to be fully generated, so who knows whether it is actually true.

> Every MCP server injects its full tool schemas into context on every turn

I consider this a bug. I'm sure the chat clients will fix this soon enough.

Something like: on each turn, a subagent searches available MCP tools for anything relevant. Usually, nothing helpful will be found and the regular chat continues without any MCP context added.

Nice project! I've been working on something very similar here https://github.com/max-hq/max

It works by schematising the upstream and making data locally synchronised + a common query language, so the longer term goals are more about avoiding API limits / escaping the confines of the MCP query feature set - i.e. token savings on reading data itself (in many cases, savings can be upwards of thousands of times fewer tokens)

Looking forward to trying this out!

Why is the concept of "MCP" needed at all? Wouldn't a single tool - web access - be enough? Then you can prompt:

    Tell me the hottest day in Paris in the
    coming 7 days. You can find useful tools
    at www.weatherforadventurers.com/tools

And then the tools url can simply return a list of urls in plain text like

    /tool/forecast?city=berlin&day=2026-03-09 (Returns highest temp and rain probability for the given day in the given city)

Which return the data in plain text.

What additional benefits does MCP bring to the table?

cool!

anthropic mentions MCPs eating up context and solutions here: https://www.anthropic.com/engineering/code-execution-with-mc...

I built one specifically for Cognition's DeepWiki (https://crates.io/crates/dw2md) -- but it's rather narrow. Something more general like this clearly has more utility.

There are a handful of these. I've been using this one: https://github.com/smart-mcp-proxy/mcpproxy-go

How is this the 5th one of these I have seen this week, is everyone just trying to make the same thing?

I may be showing my ignorance here, but wouldn't the ideal situation be for the service to use the same number of tokens no matter what client sent the query?

If the service is using more tokens to produce the same output from the same query, but over a different protocol, than the service is a scam.

For a typical B2B SaaS usecase (non technical employees) -> MCP is working great since its allows people to work in Chat interfaces (ChatGPT, Claude). They will not move to terminal UX's anytime soon.

So, I dont see why a typical productivity app build CLI than MCP. Am I missing anything?

How does this differ from mcporter? https://github.com/steipete/mcporter/

Someone had to do it. mcp in bash would make them composable, which I think is the strongest benefit for high capability agents like Claude, Cursor and the like, who can write Bash better than I. Haven't gotten into MCP since early release because of the issues you named. Nice work!

Doubtful that a 16 tokens summary is the same as she JSON tool description that uses 10x more tokens. The JSON will describe parameters in a longer way and that has probably some positive impact on accuracy

How would the LLM exactly discover such unknown CLI commands?

How is it different from 'mcporter', already included in eg. openclaw?

I kind of feel like it might be better to go from CLI to MCP.

mcp just need to add dynamic tools discovery and lazy load them, that would solve this token problem right?

MCP itself is a flawed standard to being with as I said before [0] and its wraps around an API from the start.

You might as well directly create a CLI tool that works with the AI agents which does an API call to the service anyway.

[0] https://news.ycombinator.com/item?id=44479406

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This post and the project README are obviously generated slop, which personally makes me completely skip the project altogether, even if it works.

If you want humans to spend time reading your prose, then spend time actually writing it.