Rust AI Agent Skills

rust-cargo-docs-rag-mcp is an MCP (Model Context Protocol) server that provides tools for Rust crate documentation lookup. It allows LLMs to look up documentation for Rust crates they are unfamiliar with. This README focuses on how to build, version, release, and install the project using two common paths: 1. pkgx (build/install locally from source) 2. Docker image (published to GitHub Container R

Master Rust 1.75+ with modern async patterns, advanced type system

Master Rust async programming with Tokio, async traits, error handling, and concurrent patterns. Use when building async Rust applications, implementing concurrent systems, or debugging async code.

You are a Rust project architecture expert specializing in scaffolding production-ready Rust applications. Generate complete project structures with cargo tooling, proper module organization, testing

Give your agents memory that survives the session, so they stop re-deriving what they already learned and stop repeating past mistakes. Hybrid recall (BM25 + dense + RRF), bi-temporal history, and AES-256-GCM at rest, exposed as 55+ MCP tools that work with any host. 73.8% on LongMemEval's official harness (vs Zep 63.8%, Mem0 49.0%). One binary. One file. No Docker. No Postgres. No cloud. Local-fi

A professional Model Context Protocol (MCP) server for embedded debugging with probe-rs. Provides AI assistants with comprehensive debugging capabilities for embedded systems including ARM Cortex-M, RISC-V microcontrollers with real hardware integration. - 🚀 Production Ready: Real hardware integration with 22 comprehensive debugging tools - 🔌 Multi-Probe Support: J-Link, ST-Link V2/V3, DAPLink,

A fast, lightweight MCP server for Sentry, written in Rust. Compared to the official Node.js server: - Memory: 10x less RAM usage - Startup: instant cold start - Disk: single binary, no runtime dependencies - Tokens: fewer tools = smaller tool list in context This MCP server provides tools to interact with Sentry's API: - getissuedetails - Retrieve detailed information about a Sentry issue includi

A structural codebase indexer with an MCP server for AI-assisted development. Zero runtime dependencies — uses Python's ast module for Python analysis and regex-based parsing for TypeScript/JS, Go, and Rust. Requires Python 3.11+. Indexes codebases by parsing source files into structural metadata -- functions, classes, imports, dependency graphs, and cross-file call chains -- then exposes 18 query

Production-ready Rust SDK for the Model Context Protocol (MCP) with zero-boilerplate development and progressive enhancement. Build MCP servers in seconds with automatic schema generation, type-safe handlers, and multiple transport protocols. - Rust 1.89.0+ (Edition 2024) - Check with rustc --version - Tokio async runtime Add to your Cargo.toml: Or with cargo: TurboMCP uses feature flags for progr

🚀 1:1 Optimized Rust Implementation of WCGW (What Could Go Wrong) 🚀 Winx is a specialized Model Context Protocol (MCP) server that provides high-performance tools for LLM code agents. It implements the core functionality of WCGW in pure Rust for maximum efficiency and stability. Benchmarks on i9-13900K + RTX 4090 (WSL2) - Rust 1.75+ - Linux / macOS / WSL2 Add to ~/.config/Claude/claudedesktopcon

A Rust MCP server that gives Claude (Code, Desktop, or web) read/write access to your Workflowy graph, plus a generic template for turning that raw access into a working second brain. There are two ways to use it: 1. Bare MCP server. Wire the binary into your MCP host and call the 26 tools directly. No templates, no opinions. 2. Second brain. Hand BOOTSTRAP.md to Claude. The assistant follows the

Makepad UI development skills for Rust apps: setup, patterns, shaders, packaging, and troubleshooting.

An AI coding assistant built in Rust that provides both command-line and graphical interfaces for autonomous code analysis and modification. Multi-Modal Tool Execution: Adapts to different LLM capabilities with pluggable tool invocation modes - native function calling, XML-style tags, and triple-caret blocks - ensuring compatibility across various AI providers. Real-Time Streaming Interface: Advan

Codebase intelligence for AI. Detects patterns & conventions + remembers decisions across sessions. MCP server for any IDE. Offline CLI.

A high-performance, pure Rust Model Context Protocol (MCP) server that provides persistent, semantic, and graph-based memory for AI agents. Works perfectly with: Claude Desktop Claude Code (CLI) Cline / Roo Code Any other MCP-compliant client. Unlike other memory solutions that require a complex stack (Python + Vector DB + Graph DB), this project is a single, self-contained executable. ✅ No Extern

Context compaction for AI code assistants – Give your AI structured, token-efficient access to 17+ languages including Elixir, Python, TypeScript, JavaScript, Rust, and more. Quick Install · Security · Developers · AI Assistants · Docs The core problem: AI code assistants waste context on blind searches. Grep dumps entire files when you only need a function signature, leaving less room for actual

A MCP server implementation for LongPort OpenAPI, provides real-time stock market data, provides AI access analysis and trading capabilities through MCP. - LongPort OpenAPI: https://open.longportapp.com/en/ - SDK docs: https://longportapp.github.io/openapi - Trading - Create, amend, cancel orders, query today’s/past orders and transaction details, etc. - Quotes - Real-time quotes, acquisition of h

An MCP server that provides full text search for code declarations. Uses SQLite with FTS5 and universal ctags to index and search functions, classes, structures, enums, and other code elements. Supports all languages that ctags supports including Python, C, Go, C++, JavaScript, Rust, Java, and many others. - Python 3.13 - Universal Ctags 6.2.0 - SQLite with FTS5 support (included in Python 3.13) J