What if you don't need MCP at all?

The absurdity of this response is astounding. As it's clear you have no actual interest is an honest discussion I'll just drop off here and leave you to your echo chamber.

To be fair other providers have to implement reading a skill directory and only the frontmatter of the SKILL.md and read more of it when needed. But it's a LOT simpler than implementing MCP.

> Is that just bad implementation? Where are the wasted tokens?

How wouldn't it be wasteful?

I'll try to summarize a couple sources:

https://www.anthropic.com/engineering/code-execution-with-mc...

https://blog.cloudflare.com/code-mode/

Here's what Anthropic has to say about it: As MCP usage scales, there are two common patterns that can increase agent cost and latency:

    Tool definitions overload the context window;
    Intermediate tool results consume additional tokens.
    
    [...]
    
    Tool descriptions occupy more context window space, increasing response time and costs. In cases where agents are connected to thousands of tools, they’ll need to process hundreds of thousands of tokens before reading a request.
    
    [...]
    
    Most MCP clients allow models to directly call MCP tools. For example, you might ask your agent: "Download my meeting transcript from Google Drive and attach it to the Salesforce lead."
    
    The model will make calls like:
    
      TOOL CALL: gdrive.getDocument(documentId: "abc123")
              → returns "Discussed Q4 goals...\n[full transcript text]"
                 (loaded into model context)
      
      TOOL CALL: salesforce.updateRecord(
         objectType: "SalesMeeting",
         recordId: "00Q5f000001abcXYZ",
           data: { "Notes": "Discussed Q4 goals...\n[full transcript text written out]" }
        )
        (model needs to write entire transcript into context again)
    
    Every intermediate result must pass through the model. In this example, the full call transcript flows through twice. For a 2-hour sales meeting, that could mean processing an additional 50,000 tokens. Even larger documents may exceed context window limits, breaking the workflow.
    
    With large documents or complex data structures, models may be more likely to make mistakes when copying data between tool calls.

Now, if you were to instead have the LLM write code, that code can perform whatever filtering/aggregation/transformation etc that it needs, without having to round-trip from LLM to tool(s), back and forth, and the only tokens that are consumed are those of the final result. What happens with MCP? All of the text of each MCP call is flooded into the context, only for the LLM to have to make sense of what it just read to then either regurgitate that out into a file to post process (very likely with differences/"hallucinations" slipped in), or in the usual case (I'm personifying the LLM here for rhetorical purposes) it simply tries to reason about what it read to give you the filtered/aggregated/transformed/etc result you're looking for -- again, very likely with mistakes made.

You're misinterpreting OP.

OP is saying that the models have not been trained on particular MCP use, which is why MCP servers serve up tool descriptions, which are fed to the LLM just like any other text -- that is, these descriptions consume tokens and take up precious context.

Here's a representative example, taken from a real world need I had a week ago. I want to port a code base from one language to another (ReasonML to TypeScript, for various reasons). I figure the best way to go about this would be to topologically sort the files by their dependencies, so I can start with porting files with absolutely zero imports, then port files where the only dependencies are on files I've already ported, and so on. Let's suppose I want to use Claude Code to help with this, just to make the choice of agent concrete.

How should I go about this?

The overhead of the MCP approach would be analogous to trying to cram all of the relevant files into the context, and asking Claude to sort them. Even if the context window is sufficient, that doesn't matter because I don't want Claude to "try its best" to give me the topological sort straight from its nondeterministic LLM "head".

So what did I do?

I gave it enough information about how to consult build metadata files to derive the dependency graph, and then had it write a Python script. The LLM is already trained on a massive corpus of Python code, so there's no need to spoon feed it "here's such and such standard library function", or "here's the basic Python syntax", etc -- it already "knows" that. No MCP tool descriptions required.

And then Claude code spits out a script that, yes, I could have written myself, but it does it in maybe 1 minute total of my time. I can skim the script and make sure that it does exactly what it should be doing. Given that this is code, and not nondeterministic wishy washy LLM "reasoning", I know that the result is both deterministic and correct. The total token usage is tiny.

If you look at what Anthropic and CloudFlare have to say on the matter (see https://www.anthropic.com/engineering/code-execution-with-mc... and https://blog.cloudflare.com/code-mode/), it's basically what I've described, but without explicitly telling the LLM to write a script / reviewing that script.

If you have the LLM write code to interface with the world, it can leverage its training in that code, and the code itself will do what code does (precisely what it was configured to do), and the only tokens consumed will be the final result.

MCP is incredibly wasteful and provides more opportunities for LLMs to make mistakes and/or get confused.

You are correct.

I think many here have no idea what exactly MCP is, and think it's some sort of magic sauce that transcends how LLMs usually work.

    “But Brawndo has what plants crave! It's got electrolytes! '...Okay - what are electrolytes? Do you know? Yeah. It's what they use to make Brawndo.' But why do they use them in Brawndo? What do they do?''They're part of what plants crave.'But why do plants crave them?'Because plants crave Brawndo, and Brawndo has electrolytes.”
    ― Idiocracy Movie