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Products that do what Simple to build MCP servers that easily connect with custom LLM calls does
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!
- 1MS
Hi HN! I built a custom MCP (Model Context Protocol) server that connects Blender to LLMs like ChatGPT, Claude, and any other llm supporting tool calling and mcps, enabling the AI to understand and control 3D scenes using natural language. You can describe an entire environment like: > “Create a small village with 5 huts arranged around a central bonfire, add a river flowing on the left, place a wooden bridge across it, and scatter trees randomly.” And the system parses that, reasons about the scene, and builds it inside Blender — no manual modeling or scripting needed. What it can do: -…
2025 · blender-mcp-psi.vercel.app
- 2AM
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/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 /…
2025 · github.com
- 3AM
2025 · github.com
- 4CR
Hey HN, I built pg-mcp, a Model Context Protocol (MCP) server for PostgreSQL that provides structured schema inspection and query execution for LLMs and agents. It's multi-tenant and runs over HTTP/SSE (not stdio) Features - Supports multiple database connections from multiple agents - Schema Introspection: Returns table structures, types, indexes and constraints; enriched with descriptions from pg_catalog. (for well documented databases) - Read-Only Queries: Controlled execution of queries via MCP. - EXPLAIN Tool: Helps smart agents optimize queries before execution. - Extension…
2025 · github.com
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- 8AM
Hey all - I work at Vantage, a FinOps platform. I know AI is peak hype right now. But it has definitely changed some of our dev workflows already. So we wanted to find a way to let our customers experiment with how they can use AI to make their cloud cost management work more productive. The MCP Server acts as a connector between LLMs (right now only Claude, Cursor support it but ChatGPT and Google Gemini coming soon) and your cost and usage data on Vantage which supports 20+ cloud infra providers including AWS, Datadog, Mongo, etc. (You have to have a Vantage account to use it since it's…
2025
- 9TU
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
- 10IB
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
- 11OS
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
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- 13AL
2025 · donsir.com
- 14MF
Hey everyone, I've wanted an easy way to control which mcp server tools are available to clients. So for example, I might want a gmail server to only expose the read tool (but not send, delete etc). I figured if I create a cli for spawning mcp servers, I could intercept the stdin, stdout, stderr etc and modify what the clients see when they are making calls to list tools, resources, and prompts. Well it worked! In the initial version you can easily add a server to claude with a safe list of tools: npx -y mcpgod add @modelcontextprotocol/server-everything --client claude --tools=echo,add…
2025 · github.com
- 15RA
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
- 16HM
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
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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
- 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
- 20AF
I’ve always been looking for a solution to communicate larger technical systems faster. This includes a lot of known details and a technical de-risking plan. It is clear that LLMs need that structure and are capable of digesting it well. I’ve built MCP server for guiding the Cursor IDE through the plan that comes from the LLM assisted pipeline: PRD → TRD → Project files tree → Implementation Plan 1. The whole chain comes from one end-to-end solution 2. Codebase produced is easy to navigate by the automatically managed tracebility 3. Specification updates get reflected in tasks, so the flow…
2025 · github.com
- 21AF
I built an unofficial CLI and MCP server for Lambda cloud GPU instances. The main idea: your AI agents can now spin up and manage Lambda GPUs for you. The MCP server exposes tools to find, launch, and terminate instances. Add it to Claude Code, Cursor, or any agent with one command and you can say things like "launch an H100, ssh in, and run big_job.py" Other features: - Notifications via Slack, Discord, or Telegram when instances are SSH-ready - 1Password support for API keys - Also includes a standalone CLI with the same functionality Written in Rust. MIT licensed. Note: This is an…
Jan 2026 · github.com
- 22MT
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
- 23MM
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
- 24RM
We’ve open-sourced the Robot MCP Server, a tool that lets large language models (LLMs) talk directly to robots running ROS1 or ROS2. What it does - Connects any LLM to existing ROS robots via the Model Context Protocol (MCP) - Natural language → ROS topics, services, and actions (And the ability to read any of them back) - Works without changing robot source code Why it matters - Makes robots accessible from natural language interfaces - Opens the door to rapid prototyping of AI-robot applications - We are trying to create a common interface for safe AI ↔ robot communication This is too big…
Sep 2025 · github.com
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