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somnium_sn
epistasis
I read through several of the top level pages, then SQLite, but still had no idea what was meant by "context" as it's a highly ambiguous word and is never mentioned with any concrete definition, example, or scope of capability that it is meant to imply.
After reading the Python server tutorial, it looks like there is some tool calling going on, in the old terminology. That makes more sense. But none of the examples seem to indicate what the protocol is, whether it's a RAG sort of thing, do I need to prompt, etc.
It would be nice to provide a bit more concrete info about capabilities and what the purposes is before getting into call diagrams. What do the arrows represent? That's more important to know than the order that a host talks to a server talks to a remote resource.
I think this is something that I really want and want to build a server for, but it's unclear to me how much more time I will have to invest before getting the basic information about it!
somnium_sn
Thank you. That’s good feedback.
The gist of it is: you have an llm application such as Claude desktop. You want to have it interact (read or write) with some system you have. MCP solves this.
For example you can give the application the database schema as a “resource”, effectively saying; here is a bunch of text, do whatever you want with it during my chat with the llm. Or you can give the application a tool such as query my database. Now the model itself can decide when it wants to query (usually because you said: hey tell me what’s in the accounts table or something similar).
It’s “bring the things you care about” to any llm application with an mcp client
TeMPOraL
Or, in short: it's (an attempt to create) a standard protocol to plug tools to LLM app via the good ol' tools/function calling mechanism.
It's not introducing new capabilities, just solving the NxM problem, hopefully leading to more tools being written.
(At least that's how I understand this. Am I far off?)
worldsayshi
Does it give a standard way to approve changes? I wouldn't want to give an LLM access to my database unless I can approve the changes it applies.
shenbomo
Great work on the protocol!! I am looking for some examples of creating my own custom client with the Anthropic API leveraging MCP, but I could not find any. Pretty much want to understand how Claude Desktop is integrating with MCP Server along with Anthropic API Can you provide some pointers about the integration? e.g.
import anthropic
client = anthropic.Anthropic()
response = client.messages.create( model="claude-3-5-sonnet-20241022", max_tokens=1024, [mcp_server]=... ## etc.? ... )
PeterStuer
At first glance it seems to be a proposed standard interface and protocol for describing and offering an external system to the function calling faculity of an LLM.
LordDragonfang
> had no idea what was meant by "context" as it's a highly ambiguous word and is never mentioned with any concrete definition
(forgive me if you know this and are asking a different question, but:)
I don't know how familiar you are with LLMs, but "context" used in that context generally has the pretty clear meaning of "the blob of text you give in between (the text of) the system prompt and (the text of) the user prompt"[1], which acts as context for the user's request (hence the name). Very often this is the conversation history in chatbot-style LLMs, but it can include stuff like the content of text files you're working with, or search/function results.
[1] If you want to be pedantic, technically each instance of "text" should say "tokens" there, and the maximum "context" length includes the length of both prompts.
undefined
nfw2
Here are a couple points of confusion for me:
1. The sampling documentation is confusing. "Sampling" means something very specific in statistics, and I'm struggling to see any connection between the term's typical usage and the usage here. Perhaps "prompt delegation" would be a more obvious term to use.
Another thing that's confusing about the sampling concept is that it's initiated by a server instead of a client, a reversal of how client/server interactions normally work. Without concrete examples, it's not obvious why or how a server might trigger such an exchange.
2. Some information on how resources are used would be helpful. How do resources get pulled into the context for queries? How are clients supposed to determine which resources are relevant? If the intention is that clients are to use resource descriptions to determine which to integrate into prompts, then that purpose should be more explicit.
Perhaps a bigger problem is that I don't see how clients are to take a resource's content into account when analyzing its relevance. Is this framework intentionally moving away from the practice of comparing content and query embeddings? Or is this expected to be done by indices maintained on the client?
rictic
I just want to say kudos for the design of the protocol. Seems inspired by https://langserver.org/ in all the right ways. Reading through it is a delight, there's so many tasteful little decisions.
One bit of constructive feedback: the TypeScript API isn't using the TypeScript type system to its fullest. For example, for tool providers, you could infer the type of a tool request handler's params from the json schema of the corresponding tool's input schema.
I guess that would be assuming that the model is doing constrained sampling correctly, such that it would never generate JSON that does not match the schema, which you might not want to bake into the reference server impl. It'd mean changes to the API too, since you'd need to connect the tool declaration and the request handler for that tool in order to connect their types.
jspahrsummers
This is a great idea! There's also the matter of requests' result types not being automatically inferred in the SDK right now, which would be great to fix.
Could I convince you to submit a PR? We'd love to include community contributions!
filearts
If you were willing to bring additional zod tooling or move to something like TypeBox (https://github.com/sinclairzx81/typebox), the json schema would be a direct derivation of the tools' input schemas in code.
dangsux
[dead]
dimitry12
Looking at https://github.com/modelcontextprotocol/python-sdk?tab=readm... it's clear that there must be a decision connecting, for example, `tools` returned by the MCP server and `call_tool` executed by the host.
In case of Claude Desktop App, I assume the decision which MCP-server's tool to use based on the end-user's query is done by Claude LLM using something like ReAct loop. Are the prompts and LLM-generated tokens involved inside "Protocol Handshake"-phase available for review?
LatticeAnimal
I'd love to develop some MCP servers, but I just learned that Claude Desktop doesn't support Linux. Are there any good general-purpose MCP clients that I can test against? Do I have to write my own?
(Closest I can find is zed/cody but those aren't really general purpose)
thenewwazoo
How much did you use LLMs or other AI-like tools to develop the MCP and its supporting materials?
startupsfail
Is it at least somewhat in sync with plans from Microsoft , OpenAI and Meta? And is it compatible with the current tool use API and computer use API that you’ve released?
From what I’ve seen, OpenAI attempted to solve the problem by partnering with an existing company that API-fys everything. This feels looks a more viable approach, if compared to effectively starting from scratch.
kmahorker21
What's the name of the company that OpenAI's partnered with? Just curious.
startupsfail
Zapier
computerex
It seems extremely verbose. Why does the transport mechanism matter? Would have loved a protocol/standard about how best to organize/populate the context. I think MCP touches on that but has too much of other stuff for me.
ianbutler
I’m glad they're pushing for standards here, literally everyone has been writing their own integrations and the level of fragmentation (as they also mention) and repetition going into building the infra around agents is super high.
We’re building an in terminal coding agent and our next step was to connect to external services like sentry and github where we would also be making a bespoke integration or using a closed source provider. We appreciate that they have mcp integrations already for those services. Thanks Anthropic!
bbor
I've been implementing a lot of this exact stuff over the past month, and couldn't agree more. And they even typed the python SDK -- with pydantic!! An exciting day to be an LLM dev, that's for sure. Will be immediately switching all my stuff to this (assuming it's easy to use without their starlette `server` component...)
nichochar
As someone building a client which needs to sync with a local filesystem (repo) and database, I cannot emphasize how wonderful it is that there is a push to standardize. We're going to implement this for https://srcbook.com
valtism
This is a nice 2-minute video overview of this from Matt Pocock (of Typescript fame) https://www.aihero.dev/anthropics-new-model-context-protocol...
xrd
Very nice video, thank you.
His high level summary is that this boils down to a "list tools" RPC call, and a "call tool" RPC call.
It is, indeed, very smart and very simple.
jascha_eng
Hmm I like the idea of providing a unified interface to all LLMs to interact with outside data. But I don't really understand why this is local only. It would be a lot more interesting if I could connect this to my github in the web app and claude automatically has access to my code repositories.
I guess I can do this for my local file system now?
I also wonder if I build an LLM powered app, and currently simply to RAG and then inject the retrieved data into my prompts, should this replace it? Can I integrate this in a useful way even?
The use case of on your machine with your specific data, seems very narrow to me right now, considering how many different context sources and use cases there are.
jspahrsummers
We're definitely interested in extending MCP to cover remote connections as well. Both SDKs already support an SSE transport with that in mind: https://modelcontextprotocol.io/docs/concepts/transports#ser...
However, it's not quite a complete story yet. Remote connections introduce a lot more questions and complexity—related to deployment, auth, security, etc. We'll be working through these in the coming weeks, and would love any and all input!
jascha_eng
Will you also create some info on how other LLM providers can integrate this? So far it looks like it's mostly a protocol to integrate with anthropic models/desktop client. That's not what I thought of when I read open-source.
It would be a lot more interesting to write a server for this if this allowed any model to interact with my data. Everyone would benefit from having more integration and you (anthropic) still would have the advantage of basically controlling the protocol.
somnium_sn
Note that both Sourcegraph's Cody and the Zed editor support MCP now. They offer other models besides Claude in their respective application.
The Model Context Protocol initial release aims to solve the N-to-M relation of LLM applications (mcp clients) and context providers (mcp servers). The application is free to choose any model they want. We carefully designed the protocol such that it is model independent.
nl
OpenAI has Actions which is relevant for this too: https://platform.openai.com/docs/actions/actions-library
Here's one for performing GitHub actions: https://cookbook.openai.com/examples/chatgpt/gpt_actions_lib...
mike_hearn
Local only solves a lot of problems. Our infrastructure does tend to assume that data and credentials are on a local computer - OAuth is horribly complex to set up and there's no real benefit to messing with that when local works fine.
TeMPOraL
I'm honestly happy with them starting local-first, because... imagine what it would look like if they did the opposite.
> It would be a lot more interesting if I could connect this to my github in the web app and claude automatically has access to my code repositories.
In which case the "API" would be governed by a contract between Anthropic and Github, to which you're a third party (read: sharecropper).
Interoperability on the web has already been mostly killed by the practice of companies integrating with other companies via back-channel deals. You are either a commercial partner, or you're out of the playground and no toys for you. Them starting locally means they're at least reversing this trend a bit by setting a different default: LLMs are fine to integrate with arbitrary code the user runs on their machine. No need to sign an extra contact with anyone!
bryant
> It would be a lot more interesting if I could connect this to my github in the web app and claude automatically has access to my code repositories.
From the link:
> To help developers start exploring, we’re sharing pre-built MCP servers for popular enterprise systems like Google Drive, Slack, GitHub, Git, Postgres, and Puppeteer.
jascha_eng
Yes but you need to run those servers locally on your own machine. And use the desktop client. That just seems... weird?
I guess the reason for this local focus is, that it's otherwise hard to provide access to local files. Which is a decently large use-case.
Still it feels a bit complicated to me.
singularity2001
For me it's complementary to openai's custom GPTs which are non-local.
xyc
Just tried out the puppeteer server example if anyone is interested in seeing a demo: https://x.com/chxy/status/1861302909402861905. (Todo: add tool use - prompt would be like "go to this website and screenshot")
I appreciate the design which left the implementation of servers to the community which doesn't lock you into any particular implementation, as the protocol seems to be aiming to primarily solve the RPC layer.
One major value add of MCP I think is a capability extension to a vast amount of AI apps.
xyc
Made tool use work! check out demo here: https://x.com/chxy/status/1861684254297727299
xyc
sharing the messy code here just for funsies: https://gist.github.com/xyc/274394031b41ac7e8d7d3aa7f4f7bed9
bluerooibos
Awesome!
In the "Protocol Handshake" section of what's happening under the hood - it would be great to have more info on what's actually happening.
For example, more details on what's actually happening to translate the natural language to a DB query. How much config do I need to do for this to work? What if the queries it makes are inefficient/wrong and my database gets hammered - can I customise them? How do I ensure sensitive data isn't returned in a query?
jihadjihad
One thing I am having a hard time wrapping my head around is how to reliably integrate business logic into a system like this. Just hook up my Rails models etc. and have it use those?
Let’s say I’ve got a “widgets” table and I want the system to tell me how many “deprecated widgets” there are, but there is no convenient “deprecated” flag on the table—it’s defined as a Rails scope on the model or something (business logic).
The DB schema might make it possible to run a simple query to count widgets or whatever, but I just don’t have a good mental model of how these systems might work with “business logic” type things.
thinkmorebetter
Sounds like you may want an MCP server for your Rails API instead of connecting directly to db.
merpnderp
This is exactly what I've been trying to figure out. At some point the LLM needs to produce text, even if it is structured outputs, and to do that it needs careful prompting. I'd love to see how that works.
ado__dev
You can use MCP with Sourcegraph's Cody as well
https://sourcegraph.com/blog/cody-supports-anthropic-model-c...
rahimnathwani
In case anyone else is like me and wanted to try the filesystem server before anything else, you may have found the README insufficient.
You need to know:
1. The claude_desktop_config.json needs a top-level mcpServer key, as described here: https://github.com/modelcontextprotocol/servers/pull/46/comm...
2. If you did this correctly the, after you run Claude Desktop, you should see a small 'hammer' icon (with a number next to it) next to the labs icon, in the bottom right of the 'How can Claude help you today?' box.
memothon
Yeah this was a huge foot gun
jvalencia
I don't trust an open source solution by a major player unless it's published with other major players. Otherwise, the perverse incentives are too great.
stanleydrew
What risk do you foresee arising out of perverse incentives in this case?
jvalencia
Changing license terms, aggressive changes to the API to disallow competition, horrendous user experience that requires a support contract. I really don't think there's a limit to what I've seen other companies do. I generally trust libraries that competitors are maintaining jointly since there is an incentive toward not undercutting anyone.
_rupertius
For those interested, I've been working on something related to this, Web Applets – which is a spec for creating AI-enabled components that can receive actions & respond with state:
lukekim
The Model Context server is similar to what we've built at Spice, but we've focused on databases and data systems. Overall, standards are good. Perhaps we can implement MCP as a data connector and tool.
orliesaurus
I would love to integrate this into my platform of tools for AI models, Toolhouse [1], but I would love to understand the adoption of this protocol, especially as it seems to only work with one foundational model.
punkpeye
This looks pretty awesome.
Would love to chat with you if you are open about possible collab.
I am frank [at] glama.ai
orliesaurus
Emailed
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@jspahrsummers and I have been working on this for the last few months at Anthropic. I am happy to answer any questions people might have.