Discover the Best AI Resources
Curated essentials, no noise — just what matters
Connects AI coding agents (Cursor, Claude Code) to Figma through a WebSocket bridge, letting an agent read a design and edit it programmatically. Includes a Figma plugin and 40+ MCP tools for text, styling, components, and bulk edits.
Splits LLM inference into separate prefill and decode GPU pools, then routes requests with KV-cache awareness to cut redundant recomputation. Reports up to 30x throughput on DeepSeek-R1 (GB200 NVL72) and works across TensorRT-LLM, vLLM, and SGLang.
Bridges LLM-driven AI assistants to the Unity Editor so models can create scenes, edit C# scripts, manage assets, run tests and automate game-dev workflows. Exposes 47 focused MCP tool entrypoints, supports many MCP clients, and is MIT-licensed for local use.
Autonomously executes diverse biomedical research tasks by combining LLM reasoning, retrieval-augmented planning, and code-based execution. Includes a web UI and Gradio demo, a curated Know‑How library, MCP integration, and a biology-tailored reasoning model (Biomni‑R0).
Real-time DETR detector on a DINOv2 backbone, covering detection, segmentation, and keypoints. Ships in six sizes (Nano to 2XL), beats YOLO on the COCO speed-accuracy curve, and transfers better to non-COCO real-world domains.
Connects Claude (via the Model Context Protocol) to Ableton Live so the LLM can create and edit tracks, clips, instruments, and control playback through a socket-based MCP server and an Ableton MIDI Remote Script.
Gives an LLM a browser via Playwright's accessibility tree instead of screenshots, so the model reads structured snapshots, not pixels. Actions target named elements deterministically, cutting token use and removing any need for a vision model.
Exposes AWS services to AI agents over the Model Context Protocol — querying databases, provisioning infrastructure with CDK/EKS/Lambda, and pulling live AWS docs. Each domain ships as its own server, so agents wire in only what a task needs.
Gives coding agents symbol-level codebase access via language servers (LSP), turning cross-file renames, reference lookups, and edits into precise operations instead of fragile text search. Runs as an MCP server spanning 40+ languages.
Bridges IDA Pro with language-model MCP clients so LLMs can query, inspect, modify and annotate disassemblies through a typed MCP API. Provides batch-first analysis tools (decompile, xrefs, int_convert), headless idalib support, and integrations for many MCP clients; requires commercial IDA Pro and Python 3.11+.
Gives an LLM agent direct control of iOS and Android apps over one MCP interface, across simulators, emulators, and real devices. Reads the native accessibility tree to pick elements deterministically, using screenshot coordinates only as fallback.
Turns any GitHub repo into a remote MCP server, giving AI assistants live, searchable access to that project's docs and code so they stop hallucinating outdated APIs. No install: point your IDE at gitmcp.io/owner/repo.