"Weights & Biases" matching MCP servers:

Enables LLM agents to query Weights & Biases experiments, including listing projects, runs, metrics, plotting metrics, and retrieving run details.

Enables creating and managing packing slips for shipments, tracking cartons, contents, weights, chargeable weight, and shortfalls, with reports and packing slip generation.

Enables running ML experiments from a local laptop by coordinating GitHub for code, Kaggle for data and GPU training, Weights & Biases for tracking runs, and Google Drive for small artifacts.

C++26 paper reference MCP with lookup_paper, fuzzy search, and compiler_status tools over a 216-paper ISO/IEC 14882:2026 corpus. Backs a Claude Code plugin that biases the model toward final-form C++26 idioms (reflection, contracts, std::execution senders, expansion statements, #embed).

MCP server over the open index of 1,562 certification exam blueprints across 217 certifying bodies. Search exams, pull full blueprints (domains & weights, passing scores, prerequisites, renewal), and compare certifications. Read-only, public data, no API key.

An MCP server for chemistry: it computes molecular weights and isotope distributions from chemical formulae and resolves compound name/formula lookups, backed by NIST atomic-weight data and a cached finder over multiple online and offline sources.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Enables MCP clients to query Vectorworks Spotlight fixture data from automatically exported Lightwright XML files, including counts, channels, weights, and plot QC, and to write fixture patch changes back to Vectorworks.

Enables any MCP client to turn layered PSD artwork into game-ready Spine packages by inspecting and classifying layers, rigging with meshes, bones, weights, IK, physics and animation, applying procedural or After Effects-driven FX, and running runtime and mobile-budget validation with preview output. It finishes by exporting the final .spine, JSON and atlas assets so a model can drive a full art pipeline without hand-authoring rig data.

Enables reading training history and planning complete workouts on a personal calendar, including exercises with videos, sets, reps, per-set weights, supersets, notes, and block instructions. It also supports searching the exercise library, copying or moving sessions, and retrieving performance stats, personal records, and feedback.