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Products that do what CLI-use – turn any MCP server into a CLI in one command does
Hi everyone, I built cli-use, a small Python tool that turns any MCP server into a native CLI. The idea is simple: HTTP has curl, Docker has docker, Kubernetes has kubectl — MCP should have a shell-native client too. Why I made it: MCP is useful, but using it through agents has overhead: every session pays schema discovery cost every call carries JSON-RPC framing responses are often verbose JSON when the useful output is just a line or two cli-use converts that into a terse CLI so tools can be called like normal shell commands. Example: pip install cli-use cli-use add fs /tmp cli-use fs…
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TLDR; I built a tool that turns any API into a CLI designed for ai agents --- Got tired of dealing with bloated context windows from MCP servers and skills that stuff entire API docs into the agent's context CLIs fix this, agents run a single command to self-discover everything an API has to offer So, built a tool to generate them for any api. All CLIs are written in Go, fast and lightweight, no dependencies Help text (via the --help flag) is the killer feature: all context for each command/endpoint/parameter is extracted directly from the user-facing API docs and enhanced with…
Mar 2026 · instantcli.com
- 10CF
2015 · docker-exec.github.io
- 11MT
Recently I was trying to use an MCP server to pull data from a service, but hit a limitation: the MCP didn't expose the data I needed, even though the service's REST API supported it. So I wrote a quick CLI wrapper around the API. Worked great, except Claude Code had no structured way to know what my CLI does or how to call it. For `gh` or `curl` the model can learn from the extensive training data, but for a tool I just wrote, it was stabbing in the dark. MCP solves this discovery problem, but it does it by rebuilding tool interaction from scratch: server processes, JSON-RPC transport,…
Feb 2026 · github.com
- 12OP
Hello HN, Pietro here! I've been really excited to see the recent buzz around MCP and all the cool things people are building with it. Though, the fact that you can use it only through desktop apps really seemed wrong and prevented me for trying most examples, so I wrote a simple client, then I wrapped into some class, and I ended up creating a python package that abstracts some of the async uglyness. You need: * one of those MCPconfig JSONs * 6 lines of code and you can have an agent use the MCP tools from python. The structure is simple: an MCP client creates and manages the connection and…
2025 · github.com
- 13CF
2016 · github.com
- 14WB
The latest CLI releases from google and anthropic are sweet, we wanted build one that can run any model. mcp-use-cli lets you `/model` hop between providers instantly. npm i -g @mcp-use/cli && you're done What's cool: - BYOK (your keys, encrypted locally) - Slash commands for everything - MCP protocol support for custom tools - Works with OpenAI, Anthropic, Google, Mistral, Groq, local Ollama... The whole thing's TypeScript and open source. Built this on top of our Python + TS mcp-use libs, so it speaks MCP out of the box. You can hook up filesystem tools, DB servers, whatever you…
2025 · github.com
- 15IB
TLDR: OpenAPI-MCP is a Dockerized server that dynamically generates Model Context Protocol (MCP) tool definitions directly from your Swagger/OpenAPI documentation. It allows your AI agent to seamlessly access any API without additional coding, streamlining development and eliminating repetitive manual setup. For more details, code updates-----: GitHub: ckanthony/openapi-mcp Docker Hub: ckanthony/openapi-mcp
2025 · github.com
- 16MM
Hi HN! I'm Noah, an ordinary guy that got really interested in MCP about a month ago when I downloaded Cursor. It's been super exciting to see companies around the world launch their own MCP servers empowering AI to do more. Unfortunately, I got a bit overwhelmed setting up MCP servers across my clients like Claude Desktop, Cursor, and Claude Code, so I figured I'd take a shot at building an open-source tool to help others and myself! So yeah, I built a CLI tool that enables you to quickly get MCP servers from the Web integrated with your clients like Cursor and Claude Desktop. You can use…
2025 · github.com
- 17MC
I built murl because interacting with MCP (Model Context Protocol) servers from the command line was way more painful than it needed to be. MCP uses JSON-RPC 2.0 over HTTP, so every request means hand-crafting payloads with method names, params objects, and id fields. I wanted something that felt like curl. Given an MCP server at https://mcp.deepwiki.com/mcp, murl lets you append virtual paths like /tools or /tools/read_wiki_structure that map to MCP methods. These aren't real HTTP endpoints — murl translates them into the right JSON-RPC calls behind the scenes:…
Feb 2026 · github.com
- 18CA
Fun agent I've been playing with - the idea is it only has access to a bash tool, and it's directed to create CLIs for use (with additional direction to make the CLIs composable, follow the Unix philosophy, etc). It persists these CLIs and knowledge about them get injected into the system prompt dynamically, so each time it runs it gets access to a larger and larger toolset of composable CLIs. One interesting dynamic that's emerged from this is I've started using these CLIs myself since they're the same interface for the agent or for me, and it's turned into kind of non-chat channel to…
Jan 2026 · github.com
- 19SA
The startup I work for has an internal, bash-based, cli that basically amounts to shared aliases with a common entrypoint. As the number of aliases has grown, I've had a desire to group functionality together in subcommands, add more help strings, and have better tab completion. I know I could convert it to, e.g., a python script, but I was curious what was possible if we continued to use bash. I couldn't find anything that solved those problems without lots of extra machinery. I understand why, shell scripts are generally not long, and focused on a dedicated task; adding cli features to…
Mar 2026 · github.com
- 20AA
2025 · api200.co
- 21TC
Agents can run non-interactive commands, but they often fail once a workflow needs a real terminal (SSH sessions, installers, debuggers, REPLs, TUIs). I built term-cli so an agent can drive an interactive terminal session (keystrokes in, output out, wait for prompts). And it comes with agent skill for easy integration. It supports in-band file transfer: the agent can move files through the terminal stream itself (same channel as the interactive session), which is useful when the agent doesn’t have scp/sftp, shared volumes, or direct filesystem access across boundaries. Recent example:…
Mar 2026 · github.com
- 22IC
Tired of bloated installers and complex DevOps pipelines? I built PPORT — a terminal-based messenger — to demo a crazy simple idea: 1. Instant CLI delivery over HTTP 2. Just curl or irm, nothing else 3. TypeScript on the fly via Deno 4. Live deployment without Docker or builds How it works: Visit https://pport.top Run one command (curl -fsSL pport.top | sh) PPORT streams scripts and source files dynamically based on your client (curl, browser, Deno) No packaging. No compiling. No friction. Source on GitHub: https://github.com/vseplet/pport Curious what else…
2025 · pport.top
- 23SB
Hi HN! I built a CLI tool called ShellTalk for macOS, Linux, and web (WebAssembly) that maps English text to the corresponding Bash commands. ShellTalk is written in Swift and available under the Apache 2.0 license on GitHub. I was inspired a few weeks ago after reading the Meta-Harness paper and seeing a tool called Hunch that did something similar using the Apple Foundation model. I often forget flag names and orders, but I wanted something that worked consistently. The 3B AFM worked surprisingly well with Hunch, but it felt slow and sometimes slight changes in what I wrote would result in…
Apr 2026 · barrasso.me
- 24CD
Hey folks, I've been building AI agents that need to talk to various APIs, and I got tired of writing custom integrations for every service. So I built the MCP-OpenAPI Server to solve this problem! It's a simple bridge that lets AI agents discover and use our existing OpenAPI endpoints through the Model Context Protocol. No need to write custom code for each service - just point it at the OpenAPI specs, choose which endpoints to expose, and you're good to go. What makes this different from other MCP servers is that it uses SSE transport instead of stdio, making it work well for multi-tenant…
2025 · github.com
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