Alternatives
Products that do what Let your agent build its own tools with MCPglue does
We spoke to dozens of devs trying to deploy agents in prod. We found that most of them have the following dilemma (and end up not deploying because of this): giving the agents freedom to choose from a list of tools while guaranteeing that every call stays secure, fast, and actually works. That’s why we built MCPglue. It gives you the reliability you’re looking for when deploying in prod, and agents the custom tools they need to do their job well. Here’s a walkthrough of how it works: https://www.youtube.com/watch?v=uc-jdM9XnhE MCPglue lets your agent build its own tools. It…
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Hello HN, we're Andrew and Stephen from Keyboard (https://www.keyboard.dev/). After building AI tools for the past year, we recently made a YouTube video on building MCP servers and realized MCP is a total game-changer. It essentially lets AI do anything by connecting to your apps. But the deeper we dove, the clearer it became that security and privacy were complete afterthoughts. Coming from backgrounds at Okta and Stripe, this made us pretty uncomfortable. We kept seeing the same pattern: every app needs its own MCP server, each storing sensitive tokens, with minimal…
2025 · github.com
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Hey HN! I built AgentMGMT.dev today to keep track of all those agent orchestration tools that keep popping up. I've tried a few and landed on Superset, which I'm extremely happy (and productive!) with - but I think this category of tools will be extremely important and interesting in the next couple years, so it's worth keeping an eye on all available tools and how they evolve. I will keep the site up-to-date, please help me by submitting new tools that are not yet in the list, or add any details that might help folks who are out shopping for their first/next agent orchestrator!
May 2026 · agentmgmt.dev
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Hi HN, for about a year now I've been experimenting with AI agents and building my own home ecosystem; from the start I set out with the idea of an agent that behaves like a member of the family, not as a personal agent, and this made me clash very early first with OpenClaw's builtin memory, then I tested dozens of memory plugins without ever finding one that fit my purpose, so like any good builder I made my own. First on OpenClaw, as a plugin, then the idea matured and since the beginning of this year the memory plugin has evolved into an agent agnostic MCP server. It has been running my…
Jul 2026 · github.com
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We just open-sourced the internal system we built at Assembled for running coding agents as a team. Coding agents worked well for individual engineers, but the surrounding workflow was a bit of a mess. We generally found that many engineers had different MCP connections and context for their agents, personal automations running that other people couldn’t access, and very little introspection for what a human’s input into the coding agent looked like. So we built an internal system that converted coding agents into shared team infrastructure. The system runs Codex, Claude Code, OpenCode, and…
Jun 2026
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I was tired of asking my claude code to reference my codex chats to get references to what decisions it made and why ; so I built Reference MCP It, whenever prompted establishes sessions to get direct access - been using it on my system for a bit and was super helpful so I made a repo :) Would love feedback!
Jun 2026 · github.com
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I built a browser-only studio for designing and orchestrating MCP agent systems for development and experimental purposes. The whole stack — tool authoring, multi-agent orchestration, RAG, code execution — runs from a single static HTML file via WebAssembly. No backend. The bet: WASM is a hard sandbox for free. When you generate tools with an LLM (or write them by hand), the studio AST-validates the source, registers it lazily, and JIT-compiles into Pyodide on first call. SQL tools run in DuckDB-WASM in a Web Worker. The built-in RAG uses Xenova/all-MiniLM-L6-v2 via Transformers.js for…
Apr 2026 · agentmcp.studio
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I built an MCP server that connects coding agents (Claude Code, Cursor, OpenCode, Codex) to a collaborative workspace where your team and other AI models can review what the agent is planning. The problem: When Claude Code creates an implementation plan, it lives in your terminal session. Nobody else sees it until it becomes a PR. If you want GPT to check the architecture or a teammate to flag issues, you're copy-pasting between windows. This MCP server fixes that. When your agent creates a plan, it gets shared as a collaborative thread in CoChat. Engineers comment on it, other AI models…
Feb 2026 · github.com
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Describe any AI app, Get a live, MCP-powered app in minutes
May 2026 · newagentshub.dev
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