Show HN: Mcp-use – Connect any LLM to any MCP
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.
Also, hacking an IKEA curtain with MCP is an all-time flex.
Curious if you’re planning to build infra on top or keep it strictly dev tools?
Yes we plan to do more infrastructure work for sure, the idea is that larger teams will need a centralized place where they can configure their MCPs, monitor them, and define access control rules, create agents with specific permissions and capabilities. The old infrastructure (in the dev tool sense) does not really lend itself well to this new use cases.
We are building in this direction and we plan to open source this aspect as well, for now we are working closely with few large companies to first understand their pains deeply.
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.
From a company perspective that’s huge: adding a new chatbot feature that used to take a couple of sprints and a lot of glue code can now be done in hours instead of weeks.
However, the agent is really just a wrapper of Langchain AgentExecutor. This doesn't seem like something someone would want to put into production.