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AI · alternatives · 2026

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24 alternatives to MCPlexor – MCP multiplexer that cuts agent context usage by 95%

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:…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Prices are shown for the 1 we have checked on their own sites, 1 of them free or with a free tier.

  1. 1
    mcp-usefree tier, from $25/mo▲581

    Hi HN, Luigi here. We maintain mcp-use an open-source TypeScript framework for building MCP servers and MCP Apps: https://github.com/mcp-use/mcp-use MCP is now (finally) stateless so we rewrote mcp-use v2 from scratch for the 2026-07-28 MCP spec revision: https://blog.modelcontextprotocol.io/posts/2026-07-28/ Thanks to the rebuild: - Throughput: +27% → from 8,615 to 10,982 median ops/sec - Cold launch: 2.2x faster → from 151.6 ms to 68.1 ms - Clean install: 82% smaller → from 404.6 MiB to 74.4 MiB Benchmark with methodology here:…

    2025 · manufact.com · its alternatives →

  2. 2

    Hey HN, I spent my xmas break building an agent framework called mcp-agent [1](https://github.com/lastmile-ai/mcp-agent) for Model Context Protocol [2]. It makes it easy to build AI apps with MCP servers, and implements every pattern from the popular Building Effective Agents blog [3] as well as OpenAI’s Swarm [4]. I’m sharing it early to get community feedback on where to take it from here, and to ask for contributions. For those who aren’t familiar with MCP, I think of it as a standardized interface to let AI communicate with software via tool calls, resources and…

    2025 · github.com · its alternatives →

  3. 3

    Power your AI agents with enterprise-ready tools via MCP

    2025 · merge.dev · its alternatives →

  4. 4

    Integrate B2B data to any LLM in minutes

    2025 · mcp-playground.explorium.ai · its alternatives →

  5. 5

    Hey HN! A few months ago we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server/client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default. Today we're launching a significant update: Agents as MCP servers. Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks.…

    2025 · github.com · its alternatives →

  6. 6

    Every MCP server injects its full tool schemas into context on every turn — 30 tools costs ~3,600 tokens/turn whether the model uses them or not. Over 25 turns with 120 tools, that's 362,000 tokens just for schemas. mcp2cli turns any MCP server or OpenAPI spec into a CLI at runtime. The LLM discovers tools on demand: mcp2cli --mcp https://mcp.example.com/sse --list # ~16 tokens/tool mcp2cli --mcp https://mcp.example.com/sse create-task --help # ~120 tokens, once mcp2cli --mcp https://mcp.example.com/sse create-task --title "Fix bug" No…

    Mar 2026 · github.com · its alternatives →

  7. 7
    Conduit▲137

    Fix the tool-list bloat slowing your AI agent

    Jun 2026 · toolport.app · its alternatives →

  8. 8

    Agent-ready web context for any MCP client.

    Aug 2026 · docs.firecrawl.dev · its alternatives →

  9. 9ST

    Hi! After learning about MCP, I'm really excited about the future of provider-agnostic, re-usable tooling. Unfortunately I've found that while it's easy to implement an MCP server for use with tools that support it (such as Claude Desktop), it's not as easy to implement your own support (such as integrating an MCP server into your own LLM application). We implemented a thin MCP wrapper that easily integrates with Mirascope calls so that you can hook up an MCP server and client super easily to any supported LLM provider. Excited to see what people build with this!

    2025 · mirascope.com · its alternatives →

  10. 10

    Your AI agent is burning 6x more tokens than it needs to just to browse the web. We built OpenBrowser MCP to fix that. Most browser MCPs give the LLM dozens of tools: click, scroll, type, extract, navigate. Each call dumps the entire page accessibility tree into the context window. One Wikipedia page? 124K+ tokens. Every. Single. Call. OpenBrowser works differently. It exposes one tool. Your agent writes Python code, and OpenBrowser executes it in a persistent runtime with full browser access. The agent controls what comes back. No bloated page dumps. No wasted tokens. Just the data your…

    Apr 2026 · openbrowser.me · its alternatives →

  11. 11

    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 · its alternatives →

  12. 12
    One MCP▲13

    Hey HN, I’ve been experimenting with how LLMs can dynamically use large sets of tools without needing to preload them all into context - and built one-mcp to explore that idea. one-mcp is an open source MCP server built with FastAPI that acts as a semantic index + dynamic loader for API tools. Instead of hardcoding or embedding every tool spec in an LLM session (which quickly blows up context size and costs), one-mcp lets the model search, load, and execute tools on demand — using embeddings and natural language queries. What it does: - Semantic Search for Tools: Query your API catalog with…

    2025 · github.com · its alternatives →

  13. 13

    Zero-dep CLI: one MCP config synced to every agent. A 255-tool listing costs 581 tokens, not 71,929 - schemas never enter context. - activeing123/mcptoon

    Aug 2026 · github.com · its alternatives →

  14. 14

    This is an open‑source Model Context Protocol (MCP) server that gives any LLM a sense of the passage of time. Most MCP demos wire LLMs to external data stores. That’s useful, but MCP is also a chance to give models perception — extra senses beyond the prompt text. Six functions (`current_datetime`, `time_difference`, `timestamp_context`, etc.) give Claude&#x2F;GPT real temporal awareness: It can spot pauses, reason about rhythms, and even label a chat’s “three‑act structure”. Runs locally in <60 s (Python) or via a hosted demo. If time works, what else could we surface? - Location &#x2F;…

    2025 · github.com · its alternatives →

  15. 15
    MCP360▲61

    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…

    2025 · mcp360.ai · its alternatives →

  16. 16OS

    Large Language Models (LLMs) are powerful, but they’re limited by fixed context windows and outdated knowledge. What if your AI could access live search, structured data extraction, OCR, and more—all through a standardized interface? We built the JigsawStack MCP Server, an open-source implementation of the Model Context Protocol (MCP) that lets any AI model call external tools effortlessly. Here’s what it unlocks: - Web Search & Scraping: Fetch live information and extract structured data from web pages. - OCR & Structured Data Extraction: Process images, receipts, invoices, and handwritten…

    2025 · its alternatives →

  17. 17

    Global search engine for model context protocol tools

    2025 · mcpagentseek.com · its alternatives →

  18. 18

    Hey HN, I’m Austin, founder of Salestrics (salestrics.com). The Problem: > Most AI agents today are trapped in chat windows. While models are smart enough to run complex multi-step workflows, giving them production access to business context (CRM, support, billing) usually means managing unsafe local API keys or hacking together fragile point-solution scripts. What We Built: We built Salestrics to serve as both an all-in-one revenue workspace (CRM, service desk, billing, docs, email) and a production-grade Model Context Protocol (MCP) execution proxy. How It Works: Unified Context: Instead…

    Aug 2026 · salestrics.com · its alternatives →

  19. 19

    Deploy Model Context Protocol (MCP) servers with ease. Scale your AI models seamlessly with our cutting-edge platform.

    2025 · mcp-cloud.ai · its alternatives →

  20. 20

    Model Context Protocol (MCP) is a new open standard that gives AI agents a universal interface to external tools and data. Discover how MCP empowers more powerful, autonomous AI assistants to perform real-world tasks seamlessly.

    2024 · agnt.one · its alternatives →

  21. 21

    Route 5,000+ AI tools into one. Stop LLM context bloat.

    Feb 2026 · github.com · its alternatives →

  22. 22

    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 · its alternatives →

  23. 23

    I built ContextGuard after discovering that 43% of MCP servers have critical security vulnerabilities. MCP (Model Context Protocol) is the new standard that lets Claude Clients(Desktop, Windsurf, Cursor, etc.) access external tools and data sources - think of it as a plugin system for AI assistants. The problem: When you give those clients access to your filesystem, databases, or APIs through MCP servers, you're opening up serious attack vectors. Prompt injection, data leakage, and path traversal attacks are all possible. Most developers building MCP servers don't have security expertise,…

    2025 · github.com · its alternatives →

  24. 24

    We built a reference MCP server that lets your editor&#x2F;agent learn a codebase directly from source (signatures, types, AST, comments). Docs are optional. The reference impl runs on our open-source project’s codebase. Why we built it Docs are important, but they add another abstraction layer between your code and your users. Keeping them at the right quality is hard (especially at a startup), and LLM-generated docs are often mediocre until you invest real polish. Exposing code to the model in a structured way keeps answers grounded and current, and it’s always available. You can even…

    2025 · github.com · its alternatives →

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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →