How to find LM Studio plugins and MCP servers

A developer built Local AI Tools, a free, open-source directory for discovering native LM Studio plugins and MCP servers, offering capability-based search plus compatibility, setup, runtime, and provenance information. The project aggregates public listings from the LM Studio Hub and the official MCP Registry into a single catalogue with an LM Studio-specific compatibility layer. The same developer also maintains Local Video Tools, a native plugin whose v0.1.2 early preview was validated with 4K HEVC/H.265 MOV video on Apple Silicon for local FFmpeg-based inspection, trimming, and conversion.

Originally published on sahansera.dev https://sahansera.dev/finding-lm-studio-plugins/ . You have a model running in LM Studio. Now you want it to search the web, work with files, or trim a video. Where do you find the tool that makes that possible? I've built Local AI Tools https://aitools.sahansera.dev/ to help with that step. It's a free, open-source directory where you can browse native LM Studio plugins and MCP servers, search by capability, and inspect their setup information. You don't need an account to use it. If you already know the plugin you want, a direct link is fine. This is for the stage before that: knowing what you want to do, but not what to install. Discover LM Studio plugins and MCP servers — with compatibility, setup, runtime, and provenance information in one place. Local AI Tools is an open-source discovery marketplace focused on one question: What can I add to LM Studio? LM Studio has its own native plugin ecosystem, while thousands of MCP servers live across the broader Model Context Protocol ecosystem. Finding the right tool — and understanding whether it can actually be used with LM Studio — is fragmented. Local AI Tools brings those ecosystems together into a single searchable catalogue and adds an LM Studio-specific compatibility layer on top. | Native LM Studio plugins | Discover public plugins from the LM Studio Hub and jump straight into LM Studio. | | MCP servers | Discover servers from the official MCP Registry and see whether their published metadata maps safely to an | In this Reddit discussion about LM Studio plugins https://www.reddit.com/r/LocalLLM/comments/1qdn224/lm studio plugins/ , someone asks for a central listing. They then have to clarify that they mean native plugins, because several replies point them towards MCP servers. Both can extend a local AI setup, but they're different integration types. A useful directory needs to make that distinction visible and help you understand the setup behind a promising description. Local AI Tools brings together public plugin listings from LM Studio Hub and server listings from the official MCP Registry . You can browse them together or select either type. Search terms such as video , memory , or web search give you a starting point without needing a package name. Discovery: Start with the capability you need, then check the type of integration and the setup it requires. Here's a concrete example using Local Video Tools , a native plugin I also maintain. It exposes video inspection, trimming, conversion, and FFmpeg job management to LM Studio. Inspect, trim, convert, and manage long-running FFmpeg jobs directly from LM Studio — locally , with hardware acceleration , and without holding one AI tool call open for the duration of a video encode. Try the prompts https://github.com/sahansera/lmstudio-local-video-tools -try-these-prompts · Install https://github.com/sahansera/lmstudio-local-video-tools -quick-start · How it works https://github.com/sahansera/lmstudio-local-video-tools -how-it-works · Latest release https://github.com/sahansera/lmstudio-local-video-tools/releases/tag/v0.1.2 · Roadmap https://github.com/sahansera/lmstudio-local-video-tools/docs/roadmap.md v0.1.2 Early Preview is out. The core workflow has been validated with real 4K HEVC/H.265 MOV video on Apple Silicon , including lossless clipping, accurate re-encoding, VideoToolbox conversion, progress tracking, and cancellation. This release also includes filesystem and persisted-job boundary hardening ahead of the public preview. What this is: a reliable local execution layer for concrete video operations. The model decides what operation to request; FFmpeg does the actual media processing locally. Attach a video in LM Studio and talk to it naturally: | What | |---| video . Look for sahansera ; the author matters when similarly named tools appear. The same browsing approach works for other capabilities: narrow the type, search for the task, and inspect a candidate. The directory gets you to the tool and its setup information; the upstream instructions explain how to finish configuring it. This example also shows why “there's an install button” and “everything is already set up” aren't the same thing. Native Hub plugins use LM Studio's plugin installation links. Individual plugins can still depend on software installed on your machine, as the video example does. MCP servers expose capabilities through the Model Context Protocol. LM Studio supports both local and remote MCP servers, with configuration supplied through mcp.json or an available Add to LM Studio link. The LM Studio MCP documentation https://lmstudio.ai/docs/app/mcp explains those options. For MCP listings, Local AI Tools checks whether the upstream metadata is sufficient to generate an LM Studio configuration. You'll see three outcomes: | Label | What it tells you | What to do next | |---|---|---| | LM Studio Ready | The metadata can produce a configuration without additional user-supplied values. | Review the source and runtime requirements before adding it. | | Setup required | Additional values are needed, such as credentials, paths, or arguments. | Open the details and check which inputs you need to supply. | | Compatibility unknown | There isn't enough information to determine a configuration. | Check the upstream documentation for manual setup. | The homepage initially filters for ready entries. Change the compatibility filter if you want to include tools that need setup or have unknown compatibility. An unknown label can reflect incomplete metadata, so it doesn't by itself establish that the server is incompatible. Compatibility: Generating a configuration and verifying a tool's behaviour are separate jobs. The directory helps with the first. A local model can use an integration that calls a remote service. An API key, network access, or filesystem access can therefore matter just as much as the tool's name. The directory surfaces runtime, API-key, source, and risk information where it's available. Some metadata is inferred, and these signals aren't a security audit. I haven't tested every listed tool with every model. Check the upstream project when deciding whether to install it. The practical distinction is between finding a tool, configuring it, and having your chosen model use it successfully. The catalogue helps with the first two. Actual behaviour still depends on the tool, its environment, and the model. Local AI Tools is MIT-licensed and built with Astro. Discovery and enrichment happen during the build, and the site is published as static files. The source repository is linked with this article if you'd like to inspect the implementation or contribute. Listed tools stay with their own maintainers and retain their own licenses. This is an independent community project, not affiliated with or endorsed by LM Studio. The most useful contributions are concrete: a missing plugin, an incorrect category, or a setup requirement that a listing overlooks. Include the public tool link and what needs correcting in a GitHub issue. Browse Local AI Tools https://aitools.sahansera.dev/ and search for something you'd like your local model to do. You shouldn't need to know the plugin's name before you can find it. Disclosure: This article was written with AI assistance.