Show HN: Mcp-use – Connect any LLM to any MCP
68 comments
·July 31, 2025zwaps
I get the client part, great job!
However, the agent is really just a wrapper of Langchain AgentExecutor. This doesn't seem like something someone would want to put into production.
pzullo
Valid feedback, we did not put as much work on the agent as we did for the client and MCP side yet, but we plan to write a cleaner more composable MCPAgent as well. Actually I would be super happy to hear what you consider a standard here, something like https://openai.github.io/openai-agents-python/ ?
saberience
Huge variety of problems with this for mid-market or enterprise use. This is basically a toy right now and can’t be used for solving repeatable, valuable problems for actual businesses, ie: stuff that matters.
One: dependence on langchain.
Two: Security? Observability?
Three: You have never asked yourself, why would someone want to connect an LLM to infinite random mcp servers. The vast majority (of mcp tools and servers) are insecure, vibe coded, basically terrible.
Four: There needs to be way more focus on quality versus quantity. It’s easy to connect LLMs to MCP servers, it’s not a problem companies are willing to spend much money on, the issue is ensuring LLMs call the right tools 98%+ of the time with the right parameters.
Five: There are tons and tons of existing projects for connecting LLMs to 1000s of MCP servers, it’s not a novel project, has no technical moat, and importantly, doesn’t solve a super valuable problem.
The better question to ask or problem to solve is this, given a high value problem, how do you get high values of accurate tool use, first time, while providing security and protection against side effects, jail breaking, random issues etc.
Most companies using “mcp” have a model which is using one or two tools (max) at a time and struggling making it work consistently. Giving them a meta tool to connect to 1000s of (mostly useless) tools isn’t helpful and won’t be taken seriously.
pzullo
Hey, thanks for your detailed feedback, it's helpful to be challenged. Here are some quick thoughts:
One: We've heard similar feedback on Langchain dependency. We also heard it is still widely used in enterprise settings despite its limitations. We're actively exploring alternatives, but it is a pretty crowded space and we could not find the best alternative yet. I'm curious: is there a specific solution you'd recommend? Shall we have our own LLM layer ?
Two: Agreed on observability client-side, improvements are on our roadmap, though currently prioritized lower based on user needs. Regarding security, we manage server-side risks via sandboxes, tool restrictions, and upcoming access control features. Preventing tool poisoning client-side is something we'll look into further. You have any other specific suggestions client side ?
Three: The "infinite server" scenario is not the main focus on the library, I am sorry if that is how is sounded. It is more of an interesting solution to an interesting problem that we wanted to share.
Four: Totally agree on prioritizing quality over quantity. mcp-use emphasizes flexibility and ease of integration, not necessarily connecting to numerous servers. Reliability is a server-client joint effort, when we work with companies this is one of our main focuses.
Five: While similar solutions exist, we've found our approach resonates well with users based on adoption and feedback. That said, this is not the end of the road, we are working and talking with many companies and solving many of the issues you mentioned, most are not so easy to integrate in the library and we offer only as part of our cloud offering.
Thanks again for challenging our thinking! And please if you have inputs it'd be great to have them
crackalamoo
Why is dependence on LangChain an issue?
Not that I disagree necessarily, just wondering if there's a consensus that LangChain is too opinionated/bloated/whatever for real industry applications, or if there's some other reason.
pzullo
Not original commenter here, and not by first hand experience. BUT. I got this kind of feedback from some communities, and I wanted to understand what companies think of this, I asked some dev that works in a company that sells software to enterprise he says that enterprise still use langchain mostly and they are fine with it. On a personal level I agree with the feedback in that langchain has some drawbacks, but at the same time it's a great way to get started.
preem_palver
Great idea! Definitely going to use it. What are some good reasons to prefer this over fastmcp clients? https://gofastmcp.com/clients/client
pzullo
Hey, thanks! Please let us know if we can help with anything once you get started. FastMCP is very good at servers, they just recently started to provide a client.
The client is comparable, but we support multiple connections at once, we handle task management for you (so you do not need to async with in our code), and we have an agent that you can get started with. Also I do not think FastMCP will go into the agent side of things in the Agent - Client - Server spectrum, so if you need support on that side (integrations with other frameworks, providers etc) you'll find it here :)
d4rkp4ttern
For what it’s worth, several months ago, in Langroid (an agent framework that works with any LLM) we added an adaptor using FastMCP that translates between Langroid’s Tools and MCP tools, so effectively it’s a way to connect any LLM to any MCP server.
Https://github.com/langroid/langroid
MCP integration:
pzullo
We designed this slightly differently where one can use the client directly an not only in our agent, the structure is more focused around the MCP functionality.
redhale
I'm confused -- I didn't see a single example in you readme or docs that uses the client WITHOUT your agent. Trying to understand if this is an alternative to FastMCP. I don't want your agent.
pzullo
Hey, we have an example in our readme and docs about how to build your custom agent. but you are right, we should probably fill the client section of the documentations with examples on how to use the client API in more details. Will be done!
The extent to which this is an alternative to FastMCP depends a bit on your use case. As long as you are not interested at all in any agent, they are alternative, but if you want to create an agent we will be closer to what you need. We designed our client with the creation of an agent in mind, and will continue to do so, the design is geared towards this and we have examples of how to use this in our agent.
FastMCP client is very similar today. I see the influence of our design in their implementation. We spoke to the authors a month back and the position was that they wanted something they could use to test their own servers, so the ultimate intention was different. Not sure where it is going to go.
maxarnold
Introduced the tool at Porsche last week. Looks like there might be a big corporate partnership coming up
pzullo
Nice! shoot us a message on Linkedin :)
jonfw
I have used mcp-use to write some demo functionality and it is very easy to use and works great!
pzullo
Thanks, I appreciate that!
scosman
How does the sandboxing work? Is it cross platform? Options for filesystem/netork?
pzullo
For sanboxing we are using E2B, which spins up a sandbox for the server execution, we run the mcp server command inside the sandbox and expose the stdio stream as an sse from the sandbox remote. You could potentially replace the E2B sanbox with any other. Unfortunately, mcp servers that need access to your filesystem cannot be run on a sanbdox, I believe you could do it with the network, what would be the use case?
mkagenius
> MCP-Use supports running MCP servers in a sandboxed environment using E2B's cloud infrastructure.
If you want to support a local and privacy friendly sandboxed environment for code execution, you may consider something I have built, Coderunner - https://github.com/instavm/coderunner - it uses Apple's native container for hosting a jupyter server and a headless browser.
miotts
neat idea and exec. With the # of MCPs exploding, I assume there will be different MCPs offering similar services, and selecting the "right" one will require more time for the devs. I see interesting implications in the Server Manager component that will hide the complexity under the hood (for practical and security reasons). Good job.
0xDA7A
Do you do anything to deal with the model performance degradation caused by having too many MCP tools? Would be cool to see a smart MCP router added here
pzullo
We did! Basically we have a meta layer between the Agent and the MCP servers you give to the clients.
We call this server manager, basically instead of exposing all the tools from all the servers at once to the agent we only expose 4 meta tools: - list servers() - connect to server(server_name) - search_tool(query) - disconnect from server(server_name)
So that the agent can dynamically connect to specific servers without flooding its context with all the tools.
The search tool basically performs semantic search over all the tools from all the servers returning the top N results (tools) and the server they belong to so that the agent can connect to the right server.
A demo of this is here https://www.reddit.com/r/mcp/comments/1k598v9/give_your_agen... where I hid a useful tool in a sea of useless ones (10 useful, 3000 useless) and the agent was able to find and use the right one.
jijji
What is really interesting in this article is that no where in either the github link presented nor on his web site, mcp-use.com, does he actually explain what an "MCP" server is, what it might be used for, the benefits of doing this. It seems he is so far in the weeds with this that it was an after thought to describe what any of this means or might be useful for.
pzullo
Hey jijji, fair point, I assumed that the hn audience and/or the people interacting with the website would already know about MCP.
If you're not familiar, MCP is an open-source protocol created by Anthropic and later adopted by all major model providers. It defines how LLMs communicate with external applications and services.
More specifically, MCP standardizes the interaction between an MCP server, where the business logic resides, and a client, loosely speaking an LLM that consumes it. The MCP server exposes primitives like tools, resources, and prompts, which the client can use to perform various operations. The communication protocol used is JSON-RPC 2.0, and interaction between the client and server occurs either locally through stdio streams or remotely over streamable HTTP.
Here are some of the good things about it:
Easier integration into agents: From an agent development perspective, MCP simplifies integrating external capabilities. Previously, you'd have to write custom integrations, which is sometimes difficult or limited by the availability of public APIs. Now, you can directly plug in an MCP server, if provided. if you had to write a custom integration, using MCP is beneficial as well, as it separates integration logic from agent logic, making it easy to hot swap any of the two.
Standardized interface and incentives for companies: Because MCP standardizes communication, developers can create MCP servers independently from the specific LLM or agent consuming them. This compatibility with clients like ChatGPT, Claude Desktop, and mcp-use provides a strong incentive for companies to develop MCP servers for their own applications. This is great because they are the ones that know best how to do this (and can).
Widespread Adoption: A protocol's value heavily depends on its adoption, and MCP is sticking real well. Companies, developers, and major model providers are mostly on board with MCP.
I'd love to know if somebody has other positive points or negative points about mcp and can share it here. Some are across the thread already.
Hey Pietro and Luigi here, we are the authors of mcp-use (https://github.com/mcp-use/mcp-use).
When the first MCP servers came out we were very excited about the technology, but as soon as we wanted to get our hands dirty, we found out that MCP could be used only through Claude Desktop or Cursor. As engineers, we did not like that. MCP seemed like something you wanted to use to build products and applications yourself, not something to hide behind a closed source application.
So we approached the SDK but were pretty dissatisfied with the developer experience (double async loops, lots of boilerplate). We decided to write mcp-use to make our lives easier.
mcp-use lets you connect any LLM to any MCP server in just 6 lines of code. We provide a high level abstraction over the official MCP SDK that makes your life easier and supports all the functionalities of the protocol.
Demo video here: https://www.youtube.com/watch?v=nL_B6LZAsp4.
The key abstractions we provide are called MCPClient and MCPAgent.
MCPClient takes in a set of server configurations, automatically detects the transport type and creates a background task which handles the stream from/to the server.
MCPAgent is a combination of the MCPClient, an LLM, and a custom system prompt. It consumes the MCP client by transforming the tools, resources and prompts into model agnostic tools that can be called by the LLM.
The library also contains some cool utilities:
- secure sandboxed execution of MCP servers (we know the protocol doesn't shine for security)
- meta-tools that allow the agent to search over available servers and tools (to avoid context flooding) and connect dynamically to the server it needs (you could create the omnipotent agent with this).
Some cool things we did with this: - write an agent that can use a browser and create/read linear tickets updated with latest information on the internet
- write an agent that has access to the metrics of our company to automatically create weekly reports.
- I connected an agent to an IKEA curtain I hacked an MCP on to adapt the lighting of my room from images of the lighting situation.
- recreated am open source claude code like CLI, with full MCP capability but with custom models and BYOK (https://github.com/mcp-use/mcp-use-cli).
We recently crossed 100,000 download and we are used by many organizations, including NASA!
We’d love to hear what you think of it, most importantly how we can improve it! We are happy to answer any questions and look forward to your comments.