Alternatives
Products that do what MCPfinder – An MCP server that finds and installs other MCP servers does
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…
- 1MA
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
- 2RA
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
- 3HM
Hi HN! Excited to share our MCP Server at Hyperbrowser - something we’ve been working on for a few days. We think it’s a pretty neat way to connect LLMs and IDEs like Cursor / Windsurf to the internet. Our MCP server exposes seven tools for data collection and browsing: 1. `scrape_webpage` - Extract formatted (markdown, screenshot etc) content from any webpage 2. `crawl_webpages` - Navigate through multiple linked pages and extract LLM-friendly formatted content 3. `extract_structured_data` - Convert messy HTML into structured JSON 4. `search_with_bing` - Query the web and get results…
2025 · github.com
- 4OS
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
- 5MM
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:…
Feb 2026 · mcplexor.com
- 6IB
Read this article by Cloudflare this morning https://blog.cloudflare.com/code-mode/ the main argument being that LLMs are much better at writing typescript code than tool calls because they've seen typescript code many more times. HN Discussion: https://news.ycombinator.com/item?id=45399204 https://news.ycombinator.com/item?id=45386248 Deno provides a great sandbox environment for Typescript code execution because of its permissions system which made it easy to spin up code that only has access to fetch and network calls. Stick an MCP proxy…
Sep 2025 · github.com
- 7
An OKF-backed Model Context Protocol (MCP) server delivering persistent long-term memory and SQLite FTS5 search for AI agents. - fellowgeek/mcp-memory
24d ago · github.com
- 8FA
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
- 9
Hi HN! We’re Theodore and Louis, founders of Armature (YC P26). We reconstruct the entire session behind the MCP tool calls you receive, including what the user asked their agent to do and what the agent thought. You wrap your MCP in 3 lines of code (our SDK is available in Typescript, Python and Go) and start seeing in your dashboard: - All sessions reconstructed: it’s like reading the real conversation the user had inside Claude or ChatGPT! - A ranking of your MCP most popular use cases, built from sessions clustering - The most frequent issues your users’ agents encounter so you can fix…
Aug 2026 · armature.tech
- 10MT
https://github.com/mcp-shark/mcp-shark Site: https://mcpshark.sh/ I built MCPShark, a traffic inspector for the Model Context Protocol (MCP). It sits between your editor/LLM client and MCP servers so you can: • See all MCP traffic (requests, responses, tools, resources) in one place • Debug sessions when tools don’t behave as expected • Optionally run “Smart Scan” checks to flag risky tools / configs
Dec 2025
- 11MM
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
- 12RA
Hi HN, We’re building security tooling around agentic AI systems. Today, we're releasing our public MCP catalog with detailed risk analysis for every MCP server we've found on the internet: https://mcp.armor1.ai/mcp-directory We all love agents and the power that MCPs unlock: suddenly your AI assistant can query databases, manage files, call APIs, and interact with the real world. But when we started adopting MCPs ourselves, we kept running into the same nagging questions: Is this MCP safe? Where is my data actually going? Could it execute destructive actions? Is it…
Feb 2026 · mcp.armor1.ai
- 13
- 14AL
Hi HN friends, we're Nima (nimabanai) and Craig (cbschind) from Assemble Labs (https://assemblelabs.co) building the hardware context layer for AI to help you write better firmware faster. We’ve built an MCP server that plugs into any AI tool you’re using (Cursor, Claude Code, Gemini, etc.) and brings complete hardware context (schematics, datasheets, etc.) to your existing environment (new app fatigue is real...) with accuracy and in real time. Our goal is to make writing and debugging firmware on custom hardware faster and easier. Try out the free beta release:…
Oct 2025
- 15MG
Many teams connecting LLMs to external tools eventually encounter the same architectural issue: as more tools and agents are added, the integration pattern becomes an N×M mesh of direct connections. Each agent implements its own auth, retries, rate limiting, and logging; each tool needs credentials distributed to multiple places and observability becomes fragmented. We built LLM gateway with this goal to provide a single place to manage authentication, authorization, routing, and observability for MCP servers, with a path toward a more general agent-gateway architecture in the future. The…
Dec 2025 · truefoundry.com
- 16
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
- 17LA
Hi HN, I'm excited to share Latitude Agents—the first autonomous agent platform built for the Model Context Protocol (MCP). With Latitude Agents, you can design, evaluate, and deploy self-improving AI agents that integrate directly with your tools and data. We've been working on agents for a while, and continue to be impressed by the things they can do. When we learned about the Model Context Protocol, we knew it was the missing piece to enable truly autonomous agents. MCP servers were first thought out as an extension for local AI tools (i.e Claude Desktop) so they aren't easily hostable in…
2025 · latitude.so
- 18
- 19AC
We built a reference MCP server that lets your editor/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…
Sep 2025 · github.com
- 20MS
2025 · github.com
- 21TU
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
- 22AL
Most of the MCP servers that I’ve seen are tools implemented in standalone projects. To onboard more tools (especially agents and multi-agent workflows) to MCP, I’ve been thinking it’s important to allow AI engineers to continue to prototype in their existing agent frameworks and deploy with minimal conversion when ready. We created the automcp library, which you can add as a dependency to existing projects (CrewAI, LangGraph, Llama Index, OpenAI Agents SDK, Pydantic AI, mcp-agent currently supported but more coming soon). You just need to run a CLI command to create a run_mcp.py file, make…
2025 · github.com
- 23
- 24AA
I kept copy pasting between two Claude Code instances. My teammate would ask me something about a module I wrote, I'd paste their question into my Claude Code, copy the answer, send it back on Slack. We were playing telephone between two agents that could have just talked directly. So I built AgentDM. It's a hosted messaging grid where AI agents DM each other by @alias. Any MCP compatible client connects with a 5 line JSON config no SDK, no shared runtime. This is how it works: - Each agent gets a unique @alias. - Three(main) MCP tools: send_message, read_messages, message_status. - Messages…
Apr 2026 · agentdm.ai
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