The Git Times

Microsoft updated its mcp-for-beginners repository last month with new orchestration examples, addressing growing demands for secure AI systems. The year-old curriculum remains a key resource for developers implementing the Model Context Protocol.

The project provides comprehensive Jupyter Notebook tutorials covering real-world examples in .NET, Java, TypeScript, JavaScript, Rust and Python. It walks through practical techniques for constructing modular and scalable AI workflows, starting from basic session setup through to complex service orchestration.

Emphasis is placed on security measures and maintainable code structures. Users gain experience with mcp-server and mcp-client implementations that ensure reliable context management across AI interactions.

The curriculum highlights several core areas:

• Session initialization and configuration best practices
• Cross-service communication patterns using MCP
• Security protocols for protecting sensitive model data
• Techniques for scaling workflows with increasing complexity

This update arrives as more organizations move AI prototypes into production. The concrete code samples help teams avoid common pitfalls in context handling, such as memory leaks or inconsistent state management.

By offering implementations in multiple languages, the resource supports diverse development teams. A Python engineer can quickly adapt patterns shown in the Rust examples, accelerating adoption of the protocol.

Apache Airflow continues to serve as the standard platform for programmatically authoring, scheduling, and monitoring workflows defined as code. The project’s latest release, airflowctl 0.1.3, focuses on practical improvements to daily operations rather than overhauling the core engine.

The new airflowctl auth token command prints JWT access tokens on demand, while auth login now prompts interactively for credentials when none are supplied. Support for headless environments makes the tool suitable for CI/CD scripts and automated infrastructure. Users gain an --action-on-existing-key option for pools and connections import, plus a built-in retry mechanism that reduces flakiness in integration tests.

Bug fixes correct export output when table, YAML or plain formats are specified and resolve import failures when JSON omits the extra field. Compatibility updates ensure the tool works cleanly across current Python and Kubernetes versions.

At its foundation, Airflow lets teams express workflows as DAGs in Python. The scheduler executes tasks on workers according to explicit dependencies, while the web UI provides real-time visibility and troubleshooting. These CLI enhancements tighten the feedback loop for engineers who manage production data pipelines at scale, making routine administrative work faster and less error-prone.

The release reflects Airflow’s ongoing focus on operational stability for data-heavy organizations.

The punkpeye/awesome-mcp-servers repository has added a web-based directory that automatically syncs with its curated collection of Model Context Protocol implementations. This change addresses a practical pain point for developers who previously had to navigate the raw GitHub markdown to evaluate options.

The new directory organizes servers into functional categories including browser automation, code execution, cloud platforms, biology tools, and communication services. Each entry follows a consistent legend that identifies the programming language—marked with symbols for Python, TypeScript, Go or Rust—and whether the server operates locally or in the cloud.

MCP itself is an open protocol that lets AI models securely interact with external resources through standardized servers. These range from simple file access tools to complex database connectors and API integrations. The directory distinguishes local servers, which control applications such as Chrome, from cloud servers that connect to remote services like weather APIs.

Maintainers recommend reading The State of MCP in 2025 report and testing implementations with MCP Inspector. The resource also links to complementary tutorials, such as connecting Claude Desktop to a SQLite database, and maintains sections on frameworks and community channels including the r/mcp subreddit.

The update reflects MCP's shift from experimental protocol to production tooling, as more teams require reliable ways to give models access to real-world data sources without custom integration work.

(178 words)

RTAB-Map has released version 0.23.1, refreshing its long-established SLAM toolkit with updated dependencies and broader hardware compatibility. The C++ library and standalone application produces real-time 3D maps while tracking device position using RGB-D cameras, lidar or stereo input.

Core Windows binaries now ship with OpenCV 4.7.0 including xfeatures2d and nonfree modules, PCL 1.15.0 with VTK 9.3, and Qt 6.8.3. The release adds or updates drivers for Kinect for Azure, Intel RealSense D435i and L515, Stereolabs ZED SDK 5.0.3, Orbbec Astra and multiple Kinect variants. CUDA 11.7 acceleration remains available for supported GPUs.

The software integrates directly with both ROS and ROS 2 (Humble, Jazzy, Rolling) and supports deployment on Android and iOS devices. Its graph-based optimization and strong loop-closure detection continue to minimize drift during extended mapping sessions, making it reliable for large indoor environments.

These changes matter as robotics teams adopt newer depth sensors and updated middleware. The project, maintained by IntRoLab at the University of Sherbrooke, remains a practical choice for developers needing production-ready mapping without rebuilding core algorithms from scratch.

(178 words)

Dora has released version 0.4.1, bringing targeted stability improvements to its Rust-based middleware for real-time AI robotic applications. The update fixes a daemon deadlock, resolves git dataflow issues, improves error message detection, and prevents unnecessary events from reaching source nodes.

Additional changes enhance developer experience. The dora list command now provides better output, dora --version includes detailed component information, and new simplified examples demonstrate both Python and Rust dataflows. One example shows efficient transmission of multiple NumPy arrays.

The project continues to model applications as directed graphs, enabling composable, distributed pipelines with minimal latency. Its 100% Rust implementation delivers performance 10-17x faster than ROS2 in benchmarks involving 40MB data transfers. The framework supports Python (≥3.8), Rust, and C++ APIs, with an extensive library of pre-packaged nodes for cameras, kinematics, pose estimation, and AI models.

Recent months added dora.builder for imperative Python dataflow definition, Zenoh support for distribution, and nodes for Meta SAM2, Qwen2.5, Microsoft Phi-4, and Kornia image processing. These updates make Dora more reliable for production robotics workloads while maintaining its focus on low-latency embodied AI.

The maintainers of urdf-loaders have issued v0.12.4, fixing the loader's working path resolution when instantiated multiple times. This corrects an edge case that caused asset lookup failures in applications loading several robot models or refreshing scenes dynamically.

The project supplies production-ready URDF parsers for two major platforms. Unity developers use the C# implementation to import robot kinematics and visuals directly into game-engine scenes. Web teams rely on the JavaScript loader with THREE.js to render the same files in browsers.

It includes open-sourced ATHLETE URDF files from NASA JPL. These models demonstrate a complex six-limbed rover, with _flipped variants that invert revolute joint axes to simulate legs mounted beneath the chassis.

The update matters for teams running iterative simulations. Correct path handling prevents broken references during frequent model swaps or multi-robot scenarios common in robotics prototyping. Kinematic chains, collision meshes, and visual assets now load reliably across both environments.

Eight years after its initial release, the library continues bridging ROS standards with popular 3D pipelines. Its dual-platform design eliminates duplicate parsing work for developers targeting desktop and web-based robot visualization.

**

Strix has released version 0.8.2, adding the ability to expose the Caido proxy port for human-in-the-loop operation. Security analysts can now inspect and interact with traffic generated by the autonomous AI agents as they dynamically execute target applications.

The Python-based agents run code in Docker sandboxes, identify vulnerabilities, and validate them with functional proof-of-concepts rather than static signatures. The new proxy feature lets humans guide or override agent decisions when edge cases require expert judgment.

Integration with development pipelines has been strengthened through native GitHub Actions support. Scans can run automatically on pull requests, blocking insecure changes before they reach production. Reports include concrete remediation steps and compliance-ready output.

Installation uses a one-line curl script. Users set STRIX_LLM and LLM_API_KEY environment variables to connect to OpenAI, Anthropic, Google or the Strix Router. Results are saved to a strix_runs/ directory for review.

This release also updates the google-cloud-aiplatform dependency and incorporates documentation fixes from new contributor @mason5052. The changes make the system more suitable for teams that need both automation speed and human accountability in application security testing.

(172 words)

Berty has pushed version 2.471.2, addressing GitHub workflow problems to streamline its ongoing development. The project remains focused on delivering a censorship-resistant messaging experience that operates independently of traditional network infrastructure.

At its core, Berty uses a combination of libp2p for networking, IPFS for data storage, and CRDTs for conflict-free replication. The React Native mobile app supports both online and offline modes, allowing users to exchange end-to-end encrypted messages without relying on servers or revealing personal identifiers.

The system requires no phone number or email for account creation. Instead, it generates secure keys for identity. Messages stay private even on compromised networks, with metadata reduced to the absolute minimum.

For offline scenarios, Berty employs Bluetooth Low Energy and local network discovery protocols. This makes it functional in remote areas or during network outages. The CLI tools, including berty mini and berty daemon, provide additional ways to interact with the Wesh Protocol.

Maintained by Berty Technologies, a French nonprofit, the project continues to evolve. This latest release, while minor, highlights the team's attention to development processes that support long-term innovation in privacy technology.

Community maintainers of the Proxmox VE helper scripts released updates on 21 March that improve reliability for several self-hosted applications. The changes address specific operational problems rather than adding broad new functionality.

Anytype-server now waits for MongoDB to be ready before calling rs.initiate(). Frigate received a corrected CPU model fallback path, while iSponsorBlockTV fixes both release fetching and a quoted heredoc that prevented unbound variable errors during CLI wrapper creation. Headscale gains TUN device support, allowing proper VPN operation inside LXC containers. A core adjustment adds the missing -searchdomain and -nameserver prefixes in base settings.

The scripts continue to offer one-command installation for containers and VMs running Debian, Ubuntu, Alpine and Docker. Users choose between the web installer at community-scripts.org or the local menu installed with a single command that integrates directly into the Proxmox UI. Both approaches provide simple mode for beginners and advanced options for precise configuration, along with built-in update and management functions.

The project supports Proxmox VE 8.4 through 9.1 and follows current security practices. Regular contributions via GitHub and Discord keep the collection aligned with evolving self-hosting requirements.

(178 words)

The Go programming language continues to play a pivotal role in the development of efficient and scalable software. With ongoing contributions reflected in the latest pushes to the golang/go repository, the language adapts to emerging needs in cloud and systems programming.

Designed from the start for simplicity and reliability, Go enables engineers to write code that compiles quickly and runs efficiently. Its goroutines and channels handle massive concurrency, making it suitable for network services and data processing pipelines.

Why it matters now stems from the explosion of distributed systems. In an age where applications span multiple regions and require high availability, Go's performance profile reduces operational costs while maintaining developer productivity.

Concrete details from the project highlight its practical approach:

• Native support for concurrent programming without external libraries
• Garbage collection tuned for low latency in servers
• Cross-compilation capabilities for diverse target platforms

Installation remains straightforward through official binaries available at go.dev, with source builds for unsupported platforms. The contribution process welcomes new participants while preserving the project's high standards.

This combination of technical merits explains Go's enduring presence in critical infrastructure projects and developer tooling across the industry.

Typst has released version 0.14.2 to fix a memory handling vulnerability in the wasmi WebAssembly runtime used for executing plugins. The bug, present in versions 0.14.0 and 0.14.1, occurs during memory growth when allocation fails. Although the maintainers assess it as difficult to trigger and exploit—given WebAssembly's 4GB limit and modern operating system behavior—local users should upgrade promptly. Earlier versions 0.13.1 and below are unaffected.

The Rust-based compiler remains a markup-driven typesetting system that delivers LaTeX-level capability with simpler syntax. Built-in markup handles common formatting, while functions and an integrated scripting system manage more complex requirements. Set rules configure page size, heading numbering and element appearance; show rules allow complete customisation. Mathematical equations sit between dollar signs with natural function names, and incremental compilation keeps feedback fast.

Error messages are deliberately clear. Bibliography management, plugin support and CLI tooling complete the local workflow, complementing the project's online editor. The security patch ensures safer execution of user-supplied WebAssembly modules without altering the core typesetting model that has drawn steady adoption since the project's 2019 launch.

Word count: 178

OpenSSL has released version 3.6.1, a security patch update that fixes a high-severity vulnerability in PKCS#12 MAC verification along with ten other flaws.

The update addresses improper validation of PBMAC1 parameters ([CVE-2025-11187]), a stack buffer overflow in CMS AuthEnvelopedData parsing, NULL dereferences in cipher handling, excessive memory allocation in TLS 1.3 CompressedCertificate messages, and several out-of-bounds writes and type confusion issues in PKCS7 and ASN.1 processing. Many of these bugs could lead to crashes or potential security bypasses.

OpenSSL provides the foundational toolkit for secure internet communications. Its libssl implements TLS up to 1.3, DTLS, and QUIC protocols, while libcrypto supplies a full-strength general-purpose cryptographic library that can be used independently. The project also ships a FIPS-validated cryptographic module.

The openssl command-line tool remains a standard utility for creating keys and certificates, computing digests, performing encryption, and testing protocol implementations. Descended from the SSLeay library, the project continues to maintain compatibility with decades of deployed systems while supporting modern standards.

This timely patch underscores the ongoing maintenance required for infrastructure software that protects web traffic, email, and countless applications. Operators should update promptly.

(178 words)

GPU-T is a graphics card diagnostic tool for Linux that replicates the information density of Windows' GPU-Z. Written in C# with .NET and the Avalonia UI framework, it extracts data directly from the kernel sysfs interface, graphics APIs and a custom JSON hardware database.

The application identifies exact GPU model, silicon revision, die size, transistor count and release date. A "Best Match" algorithm flags when precise silicon variants cannot be confirmed. Real-time sensors display GPU and VRAM clock speeds, hotspot and edge temperatures, fan RPM and board power draw, with the option to log readings to file.

Advanced diagnostics verify support for Vulkan, OpenCL, ROCm and ray tracing. The tool detects PCIe Resizable BAR status through direct PCI resource analysis and reports BIOS and driver versions. No root privileges are required.

Version 0.1.3 ships as a 40MB universal AppImage built with sharun, making it compatible with distributions as old as Ubuntu 14.04 and non-glibc systems such as Alpine Linux. New startup checks alert users to missing utilities including vulkaninfo and clinfo. The release also fixed crashes on systems with conflicting shared libraries and improved VA-API parsing.

The project fills a specific gap for Linux users seeking a clean, dedicated GUI for hardware verification and monitoring.

The Neural-Networks-on-Silicon repository has received its latest update, incorporating papers from the 2026 HPCA conference. This refresh highlights the project's continued relevance in a fast-moving field where hardware innovation struggles to keep pace with AI model complexity.

Maintained by Fengbin Tu, assistant professor and associate director at HKUST's Institute of Integrated Circuits and Systems, the collection serves as both archive and compass for deep learning hardware research. Tu's dual role as curator and active contributor lends unique perspective to the selections.

Organized chronologically, the repository lists influential works from major conferences. Starting with the 2014 ASPLOS paper on DianNao, it traces the development of specialized accelerators through subsequent iterations like DaDianNao and ShiDianNao. Each year section details presentations at ISSCC, ISCA, MICRO, HPCA, ASPLOS, DAC, FPGA and more.

The project has broadened from its original focus on neural network accelerators to encompass wider topics in deep learning and computer architecture. This evolution mirrors industry trends toward domain-specific architectures for AI workloads.

For practitioners, the resource offers concrete value by distilling thousands of papers into a manageable, expert-vetted list. It enables quick identification of seminal works and emerging ideas without exhaustive literature searches.

As AI deployment scales across cloud and edge environments, understanding these hardware foundations becomes increasingly important for systems builders. The repository's ongoing maintenance ensures it remains a living document of the field's progress.

Twelve years after its first commit, PgTune remains a practical resource for PostgreSQL administrators who need hardware-aware configuration without deep manual analysis. The JavaScript application, built as a progressive web app, asks for straightforward inputs—CPU cores, total memory, disk type (SSD or HDD) and workload profile—then produces tuned values for postgresql.conf.

It translates hardware data into concrete recommendations: shared_buffers sized at 25 percent of RAM on most systems, work_mem limited to avoid swapping under load, effective_cache_size set to reflect available memory, and appropriate maintenance_work_mem for vacuum and index operations. These calculations derive from the original pgtune logic but are now delivered instantly through a browser interface.

The tool matters now because hardware has changed dramatically since 2014. Servers with 64-plus cores and hundreds of gigabytes of RAM are common, while container and cloud deployments often expose misleading default resource views. Incorrect settings here create immediate bottlenecks in query throughput and connection handling.

Teams use the generated output as a starting point, then validate with pg_stat_statements and production traffic. The project accepts contributions through the standard GitHub workflow, with recent maintenance ensuring continued accuracy for current PostgreSQL versions and NVMe storage characteristics.

**

The latest update to Super Mario Bros. Remastered introduces numerous enhancements in version 1.0.2. This GDScript project built with Godot 4.6 now supports the EU ROM of the original SMB1.

Players can regenerate assets and re-verify their ROM should graphics become corrupted. Custom levels support unlimited checkpoints in any subareas, and Boo colors unlock based on completion times up to the Golden variant.

The release adds several new optional player animations and frame rate limit controls in the settings. Portable mode requires only creating a portable.txt file in the executable directory.

Improvements to Level Share Square show difficulty with skulls and ratings with stars. Browsing state restores after playing downloaded custom levels. Resource packs now support .ogg music files.

Other changes include snappy Firebar movement, adjusted mushroom bounce directions and restored developer references in levels like SMBS 4-4. The time remaining displays during marathon modes.

This ongoing project recreates Super Mario Bros., The Lost Levels, Super Mario Bros. Special and All Night Nippon with improved physics and level design. It features a full level editor, custom characters and resource packs while requiring an original NES ROM.

The open source nature invites contributions via pull requests for further fixes and features.

egui has released version 0.33.3, introducing refinements to its immediate mode GUI capabilities for Rust applications. The update addresses specific usability aspects in text interaction and testing infrastructure.

The library now treats the period as a word splitter in text navigation, aiding precise cursor control in inputs with domain names or version numbers. Selected text receives a new color treatment to improve contrast and readability.

In the ecosystem, egui_kittest adds drag-and-drop helpers and enforces consistent snapshot updates for reliable testing. The egui_extras component bumps its ehttp dependency to 0.6.0 for better web request handling.

eframe allows egui to target web via Wasm as well as native platforms like Linux, macOS, Windows and Android. Its design requires only support for drawing textured triangles, enabling easy integration into game engines and other graphics applications.

This immediate mode approach reconstructs the user interface each frame from code, eliminating much of the traditional state synchronization overhead. The result is simpler code for dynamic and responsive interfaces. The project maintains an active community through its Discord server and GitHub discussions for support and contributions.

Sponsored by the Rerun team working on multimodal data visualization, these changes reflect ongoing commitment to polish. The web demo continues to serve as a practical showcase for potential users.

Nine years after it first appeared, mxgmn/WaveFunctionCollapse has shipped version 1.00. The C# library generates bitmaps and tilemaps that remain locally similar to a single input example by enforcing two constraints: every NxN pattern in the output must exist in the input, and the distribution of those patterns must stay statistically close.

The algorithm begins with every pixel in superposition, holding real-valued probabilities for each possible color drawn from the sample. It then enters an observation-propagation loop. On each observation step it selects the unobserved NxN region with the lowest Shannon entropy, collapses it to a definite state, and propagates the resulting constraints outward. The process continues until the grid is fully observed or a contradiction appears.

Because determining whether a given input allows nontrivial solutions is NP-hard, the program cannot guarantee success. In practice contradictions remain rare. The latest release notes explicitly direct Linux and macOS users to build from source, since the bundled binaries depend on the Windows-only System.Drawing library.

The project remains a standard reference in procedural generation because it produces coherent, controllable output from minimal input without requiring large training datasets or hand-tuned rules.

Core cycle

• Observe lowest-entropy region
• Collapse according to input pattern statistics
• Propagate constraints to neighbors

**