Alternatives
Products that do what Parley – your coding agent can talk to a teammate's agent does
Hi HN, I saw one friction point when working as part of a team that uses coding agents extensively - there is nothing to enable coordination between agent used by people in a team. Many times my agent would ask me to decide upon something with a fellow teammate, for which I have to serve as the network layer. So I built Parley where agents can connect to the hub over MCP with their own team-scoped token. An agent addresses a teammate's agent by name and ask questions/handover tasks. Agents can also use file claims to signal what files they are working on, to highlight overlapping work.…
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I submitted this earlier but it didn’t get any traction. But it’s blowing up on Twitter, so I figured I would give it another shot here. The system is quick and easy to setup and works surprisingly well. And it’s not just a fun gimmick; it’s now a core part of my workflow.
Nov 2025 · github.com
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Hello HN! I wanted to share a small MCP + web app I built to solve a problem at work. Essentially, we’ve been doing great when working with agents 1:1, but collaboration has been a struggle. E.g. when I have to collaborate with a teammate and share context or handoff work usually what I would do is create a markdown with my agent, paste in slack, then my teammate will copy and paste it to their agent and vice-versa. To make our lives easier, I built AgentCouch, a “messaging app” for agents that lets our agents chat and hand off work directly in shared rooms. Humans can also watch the…
Jul 2026 · agentcouch.dev
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Single-agent LLMs suck at long-running complex tasks. We’ve open-sourced a multi-agent orchestrator that we’ve been using to handle long-running LLM tasks. We found that single LLM agents tend to stall, loop, or generate non-compiling code, so we built a harness for agents to coordinate over shared context while work is in progress. How it works: 1. Orchestrator agent that manages task decomposition 2. Sub-agents for parallel work 3. Subscriptions to task state and progress 4. Real-time sharing of intermediate discoveries between agents We tested this on a Putnam-level math problem, but the…
Feb 2026 · github.com
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Our team lives in Slack, but we don’t have access to the Slack MCP and couldn’t find anything out there that worked for us, so we coded our own agent-slack CLI * Can paste in Slack URLs * Token efficient * Zero-config (auto auth if you use Slack Desktop) Auto downloads files/snippets. Also can read Slack canvases as markdown! MIT License
Feb 2026 · github.com
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Apr 2026 · juanpabloaj.com
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Hi HN — we built agentcall.dev because the coding agent you're already running in your terminal shouldn't be trapped there. The pitch: your existing Claude Code, Codex, OpenClaw, or Cursor session joins a Google Meet, Teams, or Zoom call as itself. Same session, same context, same file access. It speaks, listens, screen-shares a localhost webpage, and can code live while you all talk about what it's building. What's actually on the call: • Voice in, voice out. Two modes — collaborative (sub-second via a voice intelligence layer tuned for latency) or direct (~2s, your coding agent itself…
Apr 2026
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We’ve been working with automating coding agents in sandboxes as of late. It’s bewildering how poorly standardized and difficult to use each agent varies between each other. We open-sourced the Sandbox Agent SDK based on tools we built internally to solve 3 problems: 1. Universal agent API: interact with any coding agent using the same API 2. Running agents inside the sandbox: Agent Sandbox provides a Rust binary that serves the universal agent API over HTTP, instead of having to futz with undocumented interfaces 3. Universal session schema: persisting sessions is always problematic, since…
Jan 2026 · github.com
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Hello, HN. I've created fast-agent to make building my own products easier - and remove the friction between defining Prompts, MCP Servers and their composition. It uses a simple, declarative style that's easy to work with and source control - with inbuilt support for the patterns in the Building Effective Agents paper. Because you can "warm-up" and interact with Agents before, during or after the workflows, it's easy to diagnose and tune Agent prompts and behaviour for later runs. Being able to set these workflows up makes LLM Context Management and Tool Selection a lot easier and can…
2025 · github.com
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