Packages

Apple's modern Swift-native testing framework, introduced in Xcode 16 alongside Swift 6. Swift Testing uses macros (@Test, @Suite, #expect, #require) instead of XCTest's class-based approach. Key improvements over XCTest: parameterized tests with @Test(arguments:), parallel test execution by default, Swift concurrency (async/await) support, better error messages from #expect macro, and trait-based test configuration. Designed to eventually replace XCTest for Swift code.

A sub-millisecond on-device RAG memory library for iOS and macOS AI agents, implemented in pure Swift with hybrid BM25 + HNSW vector search, local MiniLM embeddings, Metal GPU acceleration, token budgeting, and a single portable .wax file format — no server or API required.

Enterprise open-source infrastructure monitoring platform with JSON-RPC API for managing hosts, items, triggers, alerts, and dashboards for servers, networks, and applications.

MCP server for Zabbix — the open-source enterprise infrastructure monitoring platform. Enables AI agents to query Zabbix for host status, triggers, alerts, item data, graphs, and event history — supporting AI-driven operations monitoring, anomaly detection, and automated incident response workflows.

Core Python library for astronomy — provides tools for astronomical calculations, data formats, and coordinate systems. astropy features: astropy.units for physical unit tracking (u.meter, u.km/u.s), astropy.coordinates for sky coordinate systems (SkyCoord, FK5, ICRS, Galactic), astropy.time for precise astronomical time (Time, TimeDelta), astropy.io.fits for FITS file I/O, astropy.table for heterogeneous tabular data, astropy.wcs for world coordinate system transformations, astropy.cosmology for cosmological calculations, astropy.stats for robust statistics, Quantity objects that carry units through calculations, and coordinate frame conversions. The foundation of scientific Python astronomy.

Proc-macro crate that enables async fn in Rust traits — a feature that was missing from stable Rust until the Return Position Impl Trait (RPITIT) stabilization. async-trait transforms async fn trait methods into box-pinned futures, enabling async methods in trait definitions and implementations. Widely used in Rust async codebases where trait polymorphism and async are both needed. Note: largely superseded by native async fn in traits stabilized in Rust 1.75.

Extensible memoizing collections and decorators for Python — provides LRU, LFU, TTL, and RR cache implementations with @cached decorator. cachetools features: LRUCache (Least Recently Used eviction), LFUCache (Least Frequently Used), TTLCache (time-to-live expiration), RRCache (Random Replacement), Cache base class, @cached(cache) decorator for memoization, @cachedmethod(lambda self: self.cache) for method caching, keys parameter for custom cache key functions, lock parameter for thread safety, getsizeof for weighted caching, and MRUCache (Most Recently Used). Pure Python, no dependencies, no subprocess or network.

Python cryptography library providing both high-level recipes (Fernet symmetric encryption, X.509 certificates) and low-level primitives (AES, RSA, ECDSA, HMAC, hashing). cryptography features: Fernet for symmetric encryption (AES-128-CBC + HMAC-SHA256), MultiFernet for key rotation, RSA/EC key generation and signing, X.509 certificate creation and parsing, PKCS12 for certificate bundles, Hazmat primitives for low-level crypto (AES-GCM, ChaCha20-Poly1305, HKDF, PBKDF2, scrypt, Argon2id), serialization (PEM/DER/PKCS8), and OpenSSL bindings via cffi.

Disk and file backed cache library for Python — SQLite + filesystem storage providing persistent cache that survives process restarts. diskcache features: Cache (primary get/set/delete with SQLite+filesystem), Deque (persistent FIFO deque), Index (persistent sorted dict), FanoutCache (sharded for concurrent performance), DjangoCache integration, @memoize decorator, Cache.memoize() context manager, size-limited caching (disk quota), eviction policies (LRU/LFU), statistics, expire/clear/cull, and atomic transactions. Significantly faster than Redis for single-machine use cases.

Drop-in replacement for Node.js's built-in fs module with extra operations like recursive directory copy, move, ensure directory/file exists, and JSON read/write. fs-extra adds methods missing from the standard fs module — copy(), move(), ensureDir(), outputFile(), readJson(), writeJson() — all with Promise support. The most widely used Node.js file system utility library.

Cross-platform system and process monitoring for Python — provides CPU, memory, disk, network, and process information via unified API. psutil features: cpu_percent()/cpu_count() for CPU, virtual_memory()/swap_memory() for RAM, disk_usage()/disk_io_counters() for storage, net_io_counters()/net_connections() for network, Process class for per-process info (pid, name, cpu_percent, memory_info, status, open_files, connections), process_iter() for all processes, Popen integration, boot_time(), users(), pids(), and wait_procs(). Cross-platform: Linux, macOS, Windows, FreeBSD.

JSON Web Token (JWT) implementation for Python — encodes and decodes JWTs with various signing algorithms. PyJWT features: jwt.encode(payload, key, algorithm) for creating tokens, jwt.decode(token, key, algorithms=[]) for verification, HS256/HS384/HS512 (HMAC), RS256/RS512 (RSA), ES256/ES512 (ECDSA), PS256 (RSA-PSS), EdDSA (Ed25519), exp/nbf/iat claim validation, aud audience validation, leeway for clock skew, jwt.get_unverified_header() for algorithm inspection, and PyJWT[crypto] extra for RSA/EC support.

MCP server enabling structured spec-driven development workflows (Requirements -> Design -> Tasks) with real-time web dashboard, VSCode extension, approval workflows, and multi-language support for 11 languages.

Lightweight ASGI framework and toolkit — the foundation underlying FastAPI. starlette features: Router for URL routing, Request/Response primitives, WebSocket support, BackgroundTasks for fire-and-forget, StaticFiles for serving assets, TestClient (synchronous httpx wrapper for testing async apps), Middleware (SessionMiddleware, CORSMiddleware, GZipMiddleware, HTTPSRedirectMiddleware), mount for sub-applications, StreamingResponse for generator-based responses, FileResponse for file downloads, and JSONResponse/HTMLResponse/PlainTextResponse helpers. Used directly when FastAPI overhead is unwanted.

Structured logging library for Python — processes log events as dictionaries through a configurable processor pipeline before outputting. structlog features: bound loggers (log = structlog.get_logger(); log = log.bind(key=val)), processor pipeline (filter_by_level, add_log_level, add_logger_name, TimeStamper, JSONRenderer, ConsoleRenderer), stdlib integration (structlog.stdlib), async support, thread-local context, lazy evaluation, type-checked API, BoundLogger.new() for new instance, context variables, custom processors, and drop-in logging.getLogger() compatibility via structlog.stdlib.BoundLogger.

Any OpenAPI MCP server that automatically generates MCP tools from any OpenAPI (Swagger) specification — allowing agents to call any REST API with an OpenAPI spec without writing a custom MCP server, dynamically creating tools from endpoint definitions, parameters, and response schemas.

A content-focused web framework that ships zero JavaScript by default and enables Island Architecture, allowing React, Vue, and Svelte components to hydrate selectively.

Elixir's database toolkit and query language. Ecto provides a composable query DSL (Ecto.Query), schema definitions (Ecto.Schema), data validation with changesets (Ecto.Changeset), and database migrations. Works with PostgreSQL (ecto_sql + postgrex), MySQL, SQLite, and others via adapters. The changeset pattern decouples data validation from database operations, making it uniquely well-suited for multi-step data pipelines.

Microsoft To Do MCP server enabling AI agents to interact with Microsoft To Do task management — creating and updating tasks, reading task lists, setting due dates and reminders, and integrating Microsoft's task management platform (powered by Microsoft Graph API) into agent-driven productivity and workflow automation.

Reticle MCP server from Supercorp AI providing a streamlined interface for AI agents to interact with web APIs and external services through a unified tool abstraction layer — enabling agents to call arbitrary REST APIs through a standardized MCP interface with built-in parameter validation and response handling.