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Alternatives

Products that do what MCPlexor – MCP multiplexer that cuts agent context usage by 95% does

I built MCPlexor to solve a token waste problem I kept running into with MCP-based agents. The Problem: MCP (Model Context Protocol) is great for giving LLMs access to external tools. But if you connect multiple servers (GitHub, Linear, Postgres, Slack), you end up with 40-50k tokens of tool definitions injected into every request – before the agent even does anything. On a 200k context model, that's 25% gone. On smaller models, it's worse. And most runs only use 1-2 tools. The Solution: MCPlexor sits between your agent and your MCP servers. Instead of loading all tool definitions upfront:…

  1. 1
    Conduit137

    Fix the tool-list bloat slowing your AI agent

    Jun 2026

  2. 2

    Agent-ready web context for any MCP client.

    30d ago · docs.firecrawl.dev

  3. 3
    Toolport130

    Every tool, one port. One MCP setup for all your AI agents

    29d ago · toolport.app

  4. 4MA

    I’ve been building and using agents heavily lately. The Model Context Protocol ecosystem is growing insanely fast, but discovering and configuring new tools is still highly manual. Every time I needed to connect an agent to a new service, I had to browse registries, figure out the transport type, identify required env vars, and manually update "mcp.json" files. So I built MCPfinder. It aggregates servers from the official MCP registry, Glama, and Smithery (around 25,000 combined entries) into a deduplicated, ranked catalog. But the real twist is the DX: MCPfinder is itself an MCP server :D…

    Apr 2026 · mcpfinder.dev

  5. 5

    Work across 20+ apps in Slack with multiplayer collaboration

    Jun 2026

  6. 6
    Code Mode144

    Slash MCP token usage by 68%

    Nov 2025

  7. 7

    Your Agents. Your Business. Connected.

    Aug 2026 · salestrics.com

  8. 8MM

    Hey HN! I’m Gui from deco (decocms.com). We’ve been using this tool internally as the foundation for a few customer AI platforms, and today we’re open-sourcing it as MCP Mesh. MCP is quickly becoming the standard for agentic systems, but… once you go past a couple servers it turns into the same problems for every team: - M×N config sprawl (every client wired to every server, each with its own JSON + ports + retries) - Token + tool bloat (dumping tool definitions into every prompt doesn’t scale) - Credentials + blast radius (tokens scattered across clients, hard to audit, hard to revoke) - No…

    Dec 2025 · github.com

  9. 9

    easily run MCP (model context protocol) servers in the cloud

    2025

  10. 10UM

    Hey HN Community, I built MCP360 after spending weeks integrating APIs for an AI agent project. Each tool needed its own setup, auth, billing, and maintenance. When any APIs changed, my integrations broke. I got tired of it. MCP360 is a single gateway giving AI agents access to 100+ tools through one config block. Search engines, web scraping, SEO, e-commerce data, maps, domain tools, and more. Real example: Instead of managing Google Search, web scraping, SERP tracking, and keyword research as 4 separate subscriptions (4 bills, 4 auth systems, 4 points of failure), you connect once. Works…

    Oct 2025 · mcp360.ai

  11. 11TU

    Over the past couple weeks, l've been really immersed in learning about MCP, a new protocol for equipping any LLM with a set of tools that can run on your own machine or a remote server you control and give all kinds of superpowers to Al agents to do things like search, etc. As part of that research, l've already built one very fleshed-out and useful MCP server that l've shared here (I've added much more to it recently though!), the LLM Gateway MCP Server, which lets you use a big model to delegate to a cheaper model (and many more things in addition to that, like running automated…

    2025 · github.com

  12. 12BF

    Creating 3D is hard. LLMs seem to be getting better at tool use and spatial understanding. While MCPs have proved to be a good way to use these tools- the current methods have these challenges: - Access to scene graph and core C modules of Blender - Lack of parallelism, only way is to run blender headless - Lack of deterministic and fast verification layer - Inference stack- only way to use inference is to hook another MCP We're building Mixar, think Cursor for 3D. One access point to all generative inference, an agent to build scenes/blockouts, do boring stuff like UVs and export…

    Aug 2026 · mixar.app

  13. 13CA

    Hi HN — I'm the creator of FastMCP and wanted to share a new project we've open-sourced called Colin. I obviously love MCP, but I also use skills extremely heavily in my day-to-day work. Being exposed to both has made me very aware of a tension: - Anything with dynamic information, I ship over MCP. This takes work to set up and requires conversational boilerplate to refresh in every conversation. - Anything behavioral, I put in skills. They're lightweight, used automatically, and feel great. But I would never put dynamic information in a skill because keeping it up to date is a pain. And yet…

    Jan 2026 · github.com

  14. 14LF

    We built a no/low-code tool that lets you spin up MCPs from a single prompt. MCPs give LLMs access to tools, data, and actions—but they’re hard to build and deploy. Our tool abstracts that: describe what you want, and it auto-generates and hosts the necessary components. No UI flows, no manual chaining—just prompt and go. Examples: • Pull email, parse a DocSend, check Reddit, draft reply • Extract data from a niche site + send a Slack alert • Combine tools without writing glue code Live demo: https://www.youtube.com/watch?v=4uCiaQrgfoE Built over a weekend after getting…

    2025 · generatemcp.com

  15. 15MT

    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

  16. 16MS

    As a consultant I foot my own Cursor bills, and last month was $1,263. Opus is too good not to use, but there's no way to cap spending per session. After blowing through my Ultra limit, I realized how token-hungry Cursor + Opus really is. It spins up sub-agents, balloons the context window, and suddenly, a task I expected to cost $2 comes back at $8. My bill kept going up, but was I really going to switch to a worse model? No. So I built l6e: an MCP server that gives your agent the ability to budget. It works with Cursor, Claude Code, Windsurf, Openclaw, and every MCP-compatible application.…

    Apr 2026 · l6e.ai

  17. 17CR

    Hi HN, I'm Gzuuus, the creator of ContextVM this is my first post here, hope you find it interesting! I started building ContextVM some months ago, this is an open protocol that runs the Model Context Protocol (MCP) over Nostr. In practice, it’s a transport for MCP that lets you expose remote servers without needing a domain, inbound ports, or OAuth, clients, and servers only need an outbound internet connection. The problem I ran into: When deploying a remote MCP server you can feel the pain. You usually need a domain name, a static IP, TLS certificates, port forwarding, and some way to…

    Feb 2026

  18. 18LC

    Hi HN, I'm building Librarian (https://uselibrarian.dev/), an open-source (MIT) context management tool that stops AI agents from burning tokens by blindly re-reading their entire conversation history on every turn. The Problem: If you're building agentic loops in frameworks like LangGraph or OpenClaw, you hit two walls fast: Financial Cost: Token usage scales quadratically over long conversations. Passing the whole history every time gets incredibly expensive. Context Rot: As the context window fills up, the LLM suffers from the "Lost in the Middle" effect. Response latency…

    Feb 2026 · uselibrarian.dev

  19. 19MG

    Anthropic released the Model Context Protocol a couple weeks ago - https://www.anthropic.com/news/model-context-protocol. They have official sdks for python and typescript but nothing for go, so I wrote one! The main goal is to provide a low boilerplate sdk to write MCP servers, you can spin up a server which can give an LLM access to weather forecasts like this: https://github.com/metoro-io/mcp-golang/blob/main/examples/g... . Using it here: https://youtu.be/xaMkMl_R-0A The library handles generating all the MCP…

    2024 · github.com

  20. 20FA

    Hi HN -- Since Anthropic announced the Model Context Protocol (MCP) last week [1], I've been excited about giving Claude new capabilities through my custom servers. But while MCP is powerful, implementing the protocol correctly requires a lot of low-level boilerplate code. I found myself wanting something like FastAPI - a high-level framework that would let me focus on building features, not servers. After some hacking, I'm sharing FastMCP: a Pythonic framework for building MCP servers. FastMCP uses decorators to transform normal functions into MCP tools, resources, templates, and prompts,…

    2024 · github.com

  21. 21RM

    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

  22. 22OP

    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

  23. 23MI

    HTTP lets agents fetch pages. Cloudflare's Markdown for Agents lets them fetch more efficiently. MCP (Anthropic) connects agents to developer-defined tools. A2A (Google) lets agents delegate to other agents. But there's a missing layer: how does an agent execute a multi-step task on a website -- add to cart, fill a form, complete a checkout - with the site owner's consent and visibility? Today's agents either scrape (no consent, no structure) or the site builds a separate API (expensive, doesn't cover the long tail). The web's original protocols assumed someone is looking at a screen. That…

    Apr 2026 · rtrvr.ai

  24. 24AM

    I built a simple multi user, multi board, Task/Kanban MCP server. I have been looking for something like this to manage development agents, but I wasn't seeing anything that felt like what I wanted. So I set down and decided to vibe code an alternative. While it was an experiment at first I have been using it daily for my personal development projects and I really think there are others who might be looking for exactly this. It's 100% a WIP, but it is also very usable. I have a demo instance running at https://mootasks.dev. If you find this interesting I'd appreciate a star.…

    Apr 2026 · github.com

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