Explore
MCP servers and skills: search, filter by where they run, and compare.
sql-benchmarks-dagsterrctruta
LocalSQL Benchmarking Laboratory using Dagster for Orchestration
PythonApache-2.0★ 2Few starsNo key
huggingface-besthuggingface
MCP servers and skills: search, filter by where they run, and compare.
SQL Benchmarking Laboratory using Dagster for Orchestration
PythonApache-2.0★ 2Few starsNo key
Use when the user asks about finding the best, top, or recommended model for a task, wants to know what AI model to use, or wants to compare models by benchmark scores. Triggers on: "best model for X"
OfficialSkillApache-2.0★ 11k in collectionNo key
Pre-breach impact analysis: inventories sensitive data (PII, PHI, PCI-DSS, credentials), traces data flows, scores exposure vectors, and produces a regulatory blast radius report with fine ranges sour
OfficialSkillMIT★ 40k in collectionNo key
AssetOpsBench - Industry 4.0: A unified benchmark and framework for building, orchestrating, and evaluating domain-specific AI agents for Industry 4.0 asset operations and maintenance, with 460+ scena
OfficialPythonApache-2.0★ 2.4kNo key
Filesystem RAG benchmarks: corpus/, train.json, evaluate_rag.py (RAGAS quality). Not for prod monitoring, latency/throughput benchmarking (use rag-perf), or evals outside this repo layout.
OfficialSkillApache-2.0★ 3.6k in collectionNo key
Benchmark Jetson LLM/VLM serving performance across vLLM, llama.cpp, and Ollama with structured JSON output.
OfficialSkillApache-2.0★ 3.6k in collectionNo key
Makes your AI agent think like the laziest senior dev in the room. The best code is the code you never wrote.
SkillMIT★ 165kNo key
Fast and Accurate Code Search for Agents. Uses 99% fewer tokens than grep+read
PythonMIT★ 6.2kNo key
Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo w
PythonMIT★ 32kNo key
Creates, edits and benchmarks Agent Skills, with evals and description tuning for better triggering.
OfficialSkillApache-2.0No key
Memory and context engine + app that is extremely fast, scalable, and can be run fully locally. The Memory API for the AI era.
SkillMIT★ 31kNo key
Determines which LLM model to use for each agent spawn
OfficialSkillMIT★ 5.4k in collectionNo key
Recommend and customize Megatron Bridge library and benchmark recipes for a user's model, GPU count, hardware, sequence length, and pretrain/SFT/PEFT goal. Use when selecting a starting recipe, compar
OfficialSkillApache-2.0★ 3.6k in collectionNo key
Scale computer-use 2.0 with open-source drivers, cross-OS fleets, and benchmarks for training, evaluation, and data generation.
SkillMIT★ 30kNo key
Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario generation, or NVIDIA cuOpt.
OfficialSkillApache-2.0★ 3.6k in collectionNo key
High-performance code intelligence MCP server. Indexes codebases into a persistent knowledge graph — average repo in milliseconds. 162 languages, sub-ms queries, 99% fewer tokens. Single static binary
SkillMIT★ 47kNo key
Atomic Agent is a local-first AI agent. Runs open-weight models on your own machine via llama.cpp.
Node.jsMIT★ 3.4kNo key
Plan, configure, and chain repo-native Nemotron customization steps into single-step or multi-step pipelines: curation, translation, SFT/PEFT (AutoModel or Megatron-Bridge), pretraining/CPT, RL alignm
OfficialSkillApache-2.0★ 3.6k in collectionNo key
A cyber brain for your AI. It never forgets a detail, remembers exactly what you said, and learns how you work over time. Free, local, works with Cursor, Claude Code, Codex, OpenClaw, Hermes and more.
PythonMIT★ 911No key
Persistent file-based planning for AI coding agents and long-running tasks. Crash-proof markdown plans, session recovery after /clear and compaction, per-turn re-injection against context rot, determi
SkillMIT★ 27kNo key
A reading path for CPU performance engineering, from one instruction to production inference. Primary sources only, with a runnable benchmark for every section.
PythonMIT★ 1.2kNo key
Auditable memory layer for AI agents: zero-LLM-call local ingest (~10ms/msg, air-gapped), matches Mem0 on accuracy at ~1000x lower ingest cost, bi-temporal belief-state, MCP server. Honest LoCoMo/Long
PythonApache-2.0★ 10No key
Who stands behind it
