Alternatives
Products that do what OpenTunnel – Run Remote Commands as Local Agent Tool Calls does
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13,000+ MCP servers, skills & plugins for AI coding agents
Jul 2026 · codexmarketplaces.com
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2019 · nohq.co
- 4CA
2015 · github.com
- 5RL
Hi HN — I’m building an interoperability layer for AI agents that lets local and remote agents run inside the same network and coordinate with each other. Here is a demo: https://youtu.be/2_1U-Jr8wf4 • OpenClaw runs locally on-device • it connects to remote agents through Hybro Hub • both participate in the same workflow execution The goal is to make agent-to-agent coordination work across environments (local machines, cloud agents, MCP servers, etc). Right now most agent systems operate inside isolated runtimes. Hybro is an attempt to make them composable across boundaries.…
Apr 2026 · github.com
- 6OS
2015 · goremote.io
- 7DR
2021 · github.com
- 8RY
2020 · github.com
- 9UL
Mar 2026 · greywall.io
- 10RY
2020 · github.com
- 11GR
2021 · golangjob.xyz
- 12BA
2020 · github.com
- 13CA
Mar 2026 · github.com
- 14AR
Jul 2026 · github.com
- 15RJ
2016 · remote-all.com
- 16DA
I built an open-source desktop app for running and monitoring Python agents that talk over TCP. It works on macOS, Linux, and Windows. The basic idea is simple: if a repo has an `agent.py` entrypoint, the app can import it from GitHub, install `requirements.txt` if needed, connect it to a TCP server, and show what it is doing in one UI. Current features: * import agent repos from GitHub, including private repos * run agents through `agent.py` * optional `requirements.txt` support * optional `id.json` for agent metadata * connect agents to TCP servers * inspect message flow in one place *…
Mar 2026 · github.com
- 17HH
Jul 2026 · github.com
- 18AO
Mar 2026 · github.com
- 19OS
May 2026 · 49agents.com
- 20TO
I built DevClaw, an OpenClaw plugin that turns each Telegram group into an isolated, autonomous dev team: planner/orchestrator, DEVs, and QA all running on their own. I use it for all my development now. Issues on GitLab/GitHub are the single source of truth, and three things compound to save around 70% on tokens: model tiering (Haiku for typos, Opus for architecture), session reuse across tasks, and token-free scheduling that burns zero LLM calls for orchestration. Please try it and give some feedback. Also keen to hear from anyone running autonomous coding agents, especially what…
Feb 2026 · github.com
- 21AP
Mar 2026 · github.com
- 22WC
2019 · github.com
- 23EL
Instead of giving LLM tools SSH access or installing them on a server, the following command: $ promptctl ssh user@server makes a set of locally defined prompts "magically" appear within the remote shell as executable command line programs. For example, I have locally defined prompts for `llm-analyze-config` and `askai`. Then on (any) remote host I can: $ promptctl ssh user@host # Now on remote host $ llm-analyze-config /etc/nginx.conf $ cat docker-compose.yml | askai "add a load balancer" the prompts behind `llm-analyze-config` and `askai` execute on my local computer (even though…
Mar 2026 · docs.promptcmd.sh
- 24TT
2019 · github.com
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