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> And the moment we, as an industry, settle on something sane, I will rip out the whole thing and adopt that, because MCP brings _nothing_ to the table that I c
by alfalfasprout 1y ago
> And the moment we, as an industry, settle on something sane, I will rip out the whole thing and adopt that, because MCP brings _nothing_ to the table that I could not do with a "proper" API using completely standard tooling.
100%. I suppose I understand MCP for user-side tooling but people seem to be reinventing the wheel because they don't understand REST. making REST requests with a well defined schema from an LLM is not all that hard.
- OJFord 1y agoI don't even mind it existing, it's just the way it's presented/documented/talked about like it's some special novel important concept that baffles me, and I think makes it more confusing for developer newcomers (but fine or maybe even helpful for not-particularly-technical but AI-keen/'power' users).
- visarga 1y agoMCP is really a great leap because LLMs orchestrate across a collection of tools instead of running a scripted flow. The most obvious example is deep research, where the LLM sends initial queries, reads, then generates new queries and loops until it finds what it needs. This dynamic orchestration of the search tool is almost impossible to do in a scripted way. And it shows where the MCP value is - you just write simple tools, and AI handles the contextual application. You just make the backend, the front end is the LLM with human in the loop. I made an MCP with 2 tools - generate_node and search, and with it Claude Desktop app can create a knowledge graph complete with links and everything. It scales unbounded by context size but is read/write and smarter than RAG because it uses graph structure not just embeddings. I just made the reading and writing tools, the magic of writing the nodes, linking them up, searching and analyzing them is due to AI. And again, Claude can be very efficient at wielding these tools with zero effort on my part. That is the value of MCP.
- crashabr 1y agoCould you elaborate on why the graph structure is better than embeddings? Is it for a specific use case?
- simiones 1y agoMCP is a detail here. The exact same thing would happen if generate_node and search were exposed as REST endpoints, if Claude Desktop had used REST instead of MCP.
- bboygravity 1y agoIsn't part of the issue that LLM's are relatively bad at REST and json and all that? I remember like 2 years ago there was big hype/revolution around ChatGPT finally being able to return ONLY valid json when you asked it to. So apparently LLMs are not that good at scripting without mistakes. Having said that, I honestly have no clue what MCP looks like or is lol :p
- simiones 1y agoMCP is a form of JSON-RPC over HTTP, so I don't think it has anything to do with that.
- fennecbutt 1y agoMCP is just json. But to your last point: go look it up, have a read through their client/server implementations (for your language of choice). It doesn't actually take that long because the concept is actually rather simple, so I totally recommend it.
- visarga 1y agoMaybe not, I think they trained the model to be especially capable of MCP tool use, and generated data this way. Other formats and systems might be slightly worse, and the whole model would probably not handle such a diversity of tools if all it had was trained on much less diverse API integrations.
- fennecbutt 1y agoYes, I've had to deal with this at work as well. Much talk about MCP as if it's some mystical magical wonder, and not just concatenating a bunch of json to your prompt.
- jmward01 1y agoI personally wouldn't be surprised if the http calling abilities of LLMs end up killing MCP, or at least greatly reducing its use. If you train LLMs to start interacting with REST APIs as a great way to make them do more then a lot of the MCP use cases go away.
- cable 1y agoHATEOAS FTW
- nunodonato 1y agoI have a tool that builds HTTP requests. LLMs can use that just fine, IF they know the API spec they should connect to. And that is the problem. If you are then required to pass the specs of dozens of APIs, you are polluting the context with too much useless info. MCP simplifies that
- simiones 1y agoYou also need an MCP schema to understand what the MCP server can actually do, there is no free lunch here.
- nunodonato 1y agoyes, but in terms of token size its WAY cheaper for the AI to handle that than an OpenAPI spec
- miningape 1y agoIsn't this more a limitation of the OpenAPI spec? Something like GraphQL would probably work much better
- v3ss0n 1y agoLLM already exist that capabilities since chatgpt GPT3.5 Just they don't have tools and then, tools are simply introduced by tool calling specs and it works fine already. MCP is a wrapper around that specs nothing new
- jon-wood 1y agoI find it kind of sad that now we finally have tooling which could make use of HATEOS[1] style REST APIs, which are technically self-documenting and in practice never really took off because you need to understand the API to write a client for it, everyone ran off and designed something else instead. [1] https://en.wikipedia.org/wiki/HATEOAS https://en.wikipedia.org/wiki/HATEOAS