Skills
97,222 packaged capabilities and playbooks for agents. Install any of them with one command.
Data & databases
Python framework for single- and multi-objective optimization with evolutionary algorithms. Define vectorized objectives and constraints; solve with NSGA-II, NSGA-III, MOEA/D, GAs, or differential evolution. Analyze Pareto fronts, visualize trade-offs, customize operators and callbacks. For engineering design, hyperparameter search, and conflicting objectives. Alternatives: scipy.optimize (single-objective, gradient), platypus, jMetalPy (Java).
Qdrant vector database integration patterns with LangChain4j. Store embeddings, similarity search, and vector management for Java applications. Use when implementing vector-based retrieval for RAG systems, semantic search, or recommendation engines.
Use when building charts, data visualisations, or dashboards with Recharts. Also use when integrating Recharts with HeroUI, reviewing chart components, or creating responsive chart containers. Generates Recharts charts styled with HeroUI v3 design tokens and Tailwind CSS v4.
Reduce an unoptimized-query-oracle test failure log to the simplest possible reproduction case. Use when you have unoptimized-query-oracle*.log files from a failed roachtest and need to find the minimal SQL to reproduce the bug.
Use when the user wants to iterate on a viral-article scoring system itself, calibrate or improve a scoring prompt against labeled samples, or run batch scoring experiments on a fixed article set. Best for prompt-only scoring research where the evaluator scripts stay fixed and only the scoring rubric/prompt is meant to evolve.
When the user wants a technical site audit, crawl data analysis, location page quality checks, duplicate content detection, schema validation at scale, or internal linking analysis. Trigger on "Screaming Frog," "site crawl," "technical audit," "crawl data," "broken links," "duplicate content," "location page audit," or when analyzing exported crawl CSV/Excel files.
Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Trigger only when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do not trigger for general maintainer lists or non-security ownership questions.
Use when creating, developing, building, publishing, migrating, or reasoning about SpacetimeDB database modules. Covers local development, module build/publish flow, transactions, automatic migrations, incremental migrations, and the database cheat sheet. Triggers on: database module, spacetime publish, build module, migration, transaction, atomicity, developing module.
Use when writing SpacetimeDB reducers, lifecycle reducers, scheduled reducers, reducer context code, table mutations, indexed lookups, reducer isolation logic, or reducer error handling. Triggers on: reducer, ReducerContext, ctx, sender, client_connected, client_disconnected, init, scheduled reducer, insert row, delete row, update row.
Design, implement, review, or repair database schemas, queries, indexes, transactions, migrations, and backfills with explicit integrity and rollout constraints. Use when datastore behavior or the data lifecycle is a primary part of the task. Do not use for routine persistence calls whose schema and consistency contracts are unchanged.
Implements Syncfusion TypeScript/JavaScript (ES6+) DataManager for local/remote binding, CRUD, querying, caching, and middleware. Supports JsonAdaptor, ODataAdaptor, ODataV4Adaptor, UrlAdaptor, WebApiAdaptor, WebMethodAdaptor, RemoteSaveAdaptor, GraphQLAdaptor, CustomDataAdaptor, and CustomAdaptor. Covers Query class, filtering, sorting, paging, grouping, persistence, offline mode, caching, and error handling.
Typed chart grammar guidance for marks, scales, layouts, interaction, accessibility, rendering, and framework adapters. Use when a project uses TanStack Charts or when the task needs its setup, implementation, debugging, testing, migration, or integration guidance.
Always invoke for terrain, drainage, viewshed, or visibility analysis from elevation, even before the DEM or correct surface is chosen. Covers DTM-versus-DSM selection, slope, aspect, curvature, hillshade, conditioning, flow direction/accumulation, streams, watersheds, and catchments. Use point-cloud-lidar first only when an elevation surface must be created from LiDAR or photogrammetric points.
Cross-reference compound IDs across 20+ databases (ChEMBL, DrugBank, PubChem, ChEBI, PDB, SureChEMBL, HMDB, DrugCentral, BindingDB) via UniChem REST API. Resolve InChIKeys to source IDs, translate between source-specific IDs, find structurally related compounds by connectivity. POST with a JSON body for all cross-reference queries; only /sources is GET. No auth required.
Discover and compose geoscience skills for Python coding tasks. Use when choosing a geoscience library, finding a skill for a data format or method, or planning work across seismic, well logs, geological modelling, inversion, and other geoscience domains.
Fetch and save WeChat Official Account articles with full content and images. Supports any WeChat article URL, automatic image download, JSON export, and full-page screenshots. Use when you need to archive, save, or analyze WeChat Official Account articles.
WordPress migration and upgrade review. Use when reviewing database migrations, option versioning, upgrade routines, data backfills, dbDelta usage, release compatibility, rollback risk, or when user mentions "migration review", "upgrade routine", "dbDelta", "plugin upgrade", "data migration", "version bump", "backfill", "schema change", or "backwards compatibility". Detects unsafe migrations, missing version guards, destructive data changes, and upgrade-flow risks in WordPress code.
Scrape public posts from X.com (Twitter) users. Extracts text content, timestamps, engagement metrics (views, likes, retweets, replies), and generates direct post links. Use when user asks to scrape/fetch/analyze X.com posts or Twitter data, or mentions "整理@某人的发言" or "看看某人在X上说了什么".
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use when writing or modifying Python code that imports `xolars` — pairing an xarray Dataset with per-dimension Polars frames, constructing the `Xolars` container, selecting with isel/sel, or doing zarr+parquet round-trips via write/open. Skip for plain xarray or polars work that doesn't touch the `Xolars` class.
Research X data with Xquik, the world's fastest and cheapest X Twitter scraper service with the most complete X data. Use only when the request or active context identifies X or Twitter. Use for tweet search, tweet lookup, user discovery, profile timelines, threads, followers, trends, exports, or monitoring plans. Do not use for generic posts, other networks, or local dataset analysis that needs no X retrieval. Keep reads bounded. Require explicit confirmation before private reads, writes, persistent resources, or bulk jobs. Not affiliated with X Corp.
Query the ZINC22 virtual compound library (CartBlanche API, billions of make-on-demand + purchasable molecules). Look up substances by ZINC ID, resolve a SMILES to its ZINC ID (exact match), inspect purchasability/catalogs, and assemble compound sets for docking. Property (MW/logP) filtering is done locally with RDKit. For bioactivity use chembl-database-bioactivity; for approved drugs use drugbank-database-access.
DTC customer insights and market exploration — VOC, market size, user personas, niche analysis. Trigger words: 市场调研, market research, VOC, 用户画像, persona, TAM, 赛道分析, 选品方向, market size, user persona, customer insights, niche analysis. Route complex questions through afa first.
DTC retention and LTV growth — retention audits, RFM+LTV segmentation, micro-loyalty, subscription churn prevention, win-back. Trigger words: 留存, retention, 复购, LTV, 流失, churn, 会员, 订阅, win-back, RFM分层, repeat purchase, loyalty program, subscription retention. Route complex questions through afa first.
Operate and extend barretlee/agent-pulse, the evidence-backed AI industry intelligence system: inspect source catalog and lifecycle, collect and normalize signals, bind evidence, cluster Events, evaluate system health, generate Scout hypotheses, export the privacy-safe public site, and verify release gates. Use when the user asks to run, configure, debug, extend, or explain Agent Pulse, its collectors, Control Room, narratives, Scout, or GitHub Pages output. Triggers on: agent-pulse, Agent Pulse, evidence-backed intelligence, source catalog, signal collection, Event clustering, source audit, Scout opportunity, public export, weekly brief, or AI industry intelligence pipeline.
Alibaba Cloud EMR Serverless StarRocks development & operations assistant. Covers five scenarios: cluster connection, schema design, data ingestion, SQL development & tuning, and cluster health diagnostics. Use this Skill when users ask about StarRocks table design, writing SQL, choosing an ingestion method, query execution plans, materialized views, cluster health checks, FE/BE/CN node status, tablet health, or compaction. Typical scenarios: table design, Stream Load / Routine Load / Broker Load selection, SQL optimization, window functions, CTEs, JOIN tuning, materialized view design, cluster health inspection, node-down diagnosis. Not applicable for: StarRocks instance lifecycle management (create / scale / restart / config change / version upgrade — these are control-plane operations, please use the EMR Serverless console or the corresponding OpenAPI), or other Alibaba Cloud products (EMR Cluster, Spark, Milvus, ClickHouse, Doris, RDS, ECS).
Use when OCR-specialized extraction is needed with Alibaba Cloud Model Studio Qwen OCR models (`qwen-vl-ocr`, `qwen-vl-ocr-latest`, and snapshots), including document parsing, table parsing, multilingual OCR, formula recognition, and key information extraction.
Accesses stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, company fundamentals, news sentiment, and 50+ technical indicators via the Alpha Vantage REST API (free API key from alphavantage.co; realtime/intraday data and full daily history need a premium key). Use when fetching stock prices (OHLCV), company fundamentals (income statement, balance sheet, cash flow), earnings, options data, market news/sentiment, insider transactions, GDP, CPI, treasury yields, gold/silver/oil prices, Bitcoin/crypto prices, forex exchange rates, or calculating technical indicators (SMA, EMA, MACD, RSI, Bollinger Bands). Part of the AlterLab Academic Skills suite.
Integrates the Benchling R&D platform via its REST API and SDK — access the registry (DNA, proteins), inventory, ELN entries and workflows, build Benchling Apps, and query the Benchling Data Warehouse. Use when automating Benchling lab data management, syncing sample registry or inventory records, scripting ELN entries/workflows, or running SQL against the Benchling Data Warehouse. Part of the AlterLab Academic Skills suite.
Search scientific papers and retrieve structured experimental evidence extracted from full-text studies via the BGPT MCP server (`search_papers`, plus `lookup_paper` by DOI), returning 25+ fields per paper (methods, results, sample sizes, quality scores, limitations, conclusions). Use when running a literature review or evidence synthesis, or when needing experimental details (sample sizes, effect sizes, methods, quality scores) that abstracts alone do not provide. Part of the AlterLab Academic Skills suite.
Query BindingDB for measured protein-ligand binding affinities (Ki, Kd, IC50, EC50) via its keyless REST API or the full TSV download, searching by target (UniProt ID), compound (SMILES), or pathogen. Use when looking up experimental binding constants, profiling inhibitors of a protein target, doing lead optimization, polypharmacology analysis, or structure-activity relationship (SAR) studies; for curated bioactivity mining or drug-like compound library screening at scale prefer alterlab-chembl instead. Part of the AlterLab Academic Skills suite.
Access the BRENDA enzyme database via its SOAP API to retrieve kinetic parameters (Km, kcat, Ki), reaction equations, organism data, and substrate-specific enzyme information indexed by EC number. Use when looking up enzyme kinetics, turnover numbers, or substrate specificity for biochemical research and metabolic pathway analysis. Part of the AlterLab Academic Skills suite.
Query ChEMBL via the chembl_webresource_client Python client for curated bioactive molecules and drug-like compound libraries at scale — search compounds by structure or physicochemical properties, retrieve bioactivity measurements (IC50, Ki, EC50), and find inhibitors of a target. Use when screening chemical libraries, mining curated bioactivity for a protein, running SAR studies, or sourcing medicinal-chemistry data; for measured protein-ligand binding affinities (Ki/Kd/IC50) prefer alterlab-bindingdb instead. Part of the AlterLab Academic Skills suite.
Generates professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings — biomarker-stratified patient cohort analyses with outcomes and evidence-based treatment recommendation reports with decision algorithms, supporting GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance, output as publication-ready LaTeX/PDF. Use when building a CDS document, cohort analysis, or treatment recommendation report for drug development, clinical research, or evidence synthesis, or when GRADE grading, hazard ratios, survival/waterfall plots, or biomarker stratification are requested. Part of the AlterLab Academic Skills suite.
Query ClinicalTrials.gov via its API v2 to search trials by condition, drug, location, recruitment status, or phase and retrieve trial details by NCT ID. Use when finding interventional or observational studies, checking trial status and eligibility for patient matching, or exporting clinical trial records for research. Part of the AlterLab Academic Skills suite.
Access ClinPGx pharmacogenomics data (the successor to PharmGKB) to query gene-drug interactions, CPIC/DPWG dosing guidelines, drug labels, and pharmacogene records. Use when interpreting pharmacogenes (CYP2D6, CYP2C19, TPMT, DPYD, SLCO1B1), looking up genotype-guided drug dosing, checking PGx drug-safety associations (e.g. HLA-B*57:01 and abacavir), or supporting precision medicine and clinical pharmacogenomics decisions. For star-allele definitions/frequencies see PharmVar; for germline/somatic variant pathogenicity see alterlab-clinvar. Part of the AlterLab Academic Skills suite.
Query NCBI ClinVar via the E-utilities API or FTP for the clinical significance (pathogenicity) of human germline genetic variants, searching by gene, variant, condition, or genomic position and interpreting ACMG/AMP classifications and review-status star ratings. Use when assessing whether a variant is pathogenic, likely pathogenic, VUS, likely benign, or benign, resolving conflicting interpretations, or annotating a VCF with ClinVar clinical significance. For population allele frequencies by ancestry use alterlab-gnomad; for somatic cancer mutation frequencies use alterlab-cosmic. Part of the AlterLab Academic Skills suite.
Access the COSMIC catalogue of somatic mutations in cancer to query somatic mutations, the Cancer Gene Census, mutational signatures, and gene fusions (authentication required). Use when curating known cancer driver genes, looking up recurrent somatic mutations in a gene, or interpreting mutational signatures for cancer research and precision oncology. Not for germline pathogenicity calls (use alterlab-clinvar) or interactive cohort visualization like OncoPrints and survival from study data (use alterlab-cbioportal). Part of the AlterLab Academic Skills suite.
Scales pandas/NumPy workflows beyond memory with Dask distributed computing — parallel DataFrames, arrays, delayed task graphs, and cluster execution. Use when existing pandas/NumPy code must run on larger-than-RAM data or across clusters, for parallel file processing, distributed ML, or integration with existing pandas code. For out-of-core analytics on a single machine prefer vaex; for in-memory speed prefer polars. Part of the AlterLab Academic Skills suite.
Wraps RDKit in a high-level, pandas-friendly datamol interface with sensible defaults for everyday drug discovery — SMILES/SDF loading into DataFrames, molecule standardization, descriptors, fingerprints, Butina clustering, 3D conformer generation, scaffold analysis, and parallel batch processing, returning native rdkit.Chem.Mol objects. Use when running standard cheminformatics pipelines on molecule tables with minimal boilerplate; for low-level control, custom sanitization, or specialized algorithms prefer alterlab-rdkit. Part of the AlterLab Academic Skills suite.
Runs molecular machine learning with DeepChem — diverse featurizers, pre-built MoleculeNet benchmark datasets, and pre-trained models (ChemBERTa, GROVER) for property prediction (ADMET, toxicity, solubility) via traditional ML or graph neural networks. Use when running end-to-end molecular ML experiments that need MoleculeNet benchmarks, scaffold splitting, or ready-made models with minimal setup; for building custom PyTorch graph architectures prefer alterlab-torch-geometric, and for standalone molecule-to-feature-vector generation prefer alterlab-molfeat. Part of the AlterLab Academic Skills suite.
Runs Denario (AstroPilot-AI), a multiagent AI system for scientific research assistance that automates end-to-end research workflows from a described dataset through idea, methodology, computational results, and a publication-ready LaTeX paper. Built on AG2 + LangGraph with a cmbagent analysis backend. Use when driving the Denario pipeline (Denario.get_idea/get_method/get_results/get_paper), generating research ideas from a dataset description, auto-developing methodology, executing analysis agents, or emitting a journal-formatted (APS/AAS/JHEP/ICML/NeurIPS/PASJ) LaTeX manuscript. Part of the AlterLab Academic Skills suite.
Develops and runs genomics pipelines on the DNAnexus cloud platform using the dxpy Python SDK and dx CLI — build apps/applets, write dxapp.json, upload/download data, and execute jobs/workflows over FASTQ/BAM/VCF files. Use when building or running a DNAnexus app, applet, or workflow, writing dxapp.json, using dx-app-wizard or dx build, calling dxpy (find_data_objects, DXApplet.run, upload_local_file), or uploading/downloading sequencing data on DNAnexus. For LatchBio (Latch SDK @workflow/@task, LatchFile) use alterlab-latchbio instead; for Benchling LIMS use alterlab-benchling. Part of the AlterLab Academic Skills suite.
Access and analyze drug information from the DrugBank database — drug properties, interactions, targets, pathways, chemical structures, and pharmacology data. Use when working with pharmaceutical data, drug discovery research, drug-drug interaction analysis, target identification, chemical similarity searches, ADMET predictions, or any task needing detailed drug and drug-target records from DrugBank. Part of the AlterLab Academic Skills suite.
Access the European Nucleotide Archive (ENA) via its API and FTP to retrieve DNA/RNA sequences, raw sequencing reads (FASTQ), and genome assemblies by accession, with support for multiple formats. Use when downloading reads or sequences for a study, run, or sample accession, or when sourcing nucleotide data for genomics and bioinformatics pipelines. Part of the AlterLab Academic Skills suite.
Manipulate, annotate, and render phylogenetic trees programmatically with the ETE Toolkit (ete3) — parse and edit Newick/NHX, detect duplication/speciation events, infer orthology and paralogy, query NCBI taxonomy, and export PDF/SVG figures. Use when traversing or reformatting tree files, doing phylogenomic comparative analysis, or producing publication tree graphics in Python. Part of the AlterLab Academic Skills suite.
Query the openFDA API for drugs, medical devices, adverse event reports, recalls, regulatory submissions (510k, PMA), and substance identification (UNII). Use when searching FDA safety data, pharmacovigilance and adverse-event signals, device clearances, drug labels, or recall records for regulatory data analysis and safety research. Part of the AlterLab Academic Skills suite.
Parse and write FCS (Flow Cytometry Standard) files v2.0-3.1 with FlowIO — extract event data as NumPy arrays, read $-keyword metadata and channel/parameter definitions, and convert events to CSV or pandas DataFrame. Use when loading raw .fcs flow-cytometry files, inspecting channels and metadata, or preprocessing cytometry data for downstream gating and analysis. Part of the AlterLab Academic Skills suite.
Query NCBI Gene via the E-utilities and Datasets APIs, searching by gene symbol or Gene ID and retrieving gene information (RefSeqs, GO terms, genomic locations, associated phenotypes) including batch lookups. Use when resolving gene symbols to IDs, annotating gene lists, or pulling functional and positional gene metadata for downstream analysis. Part of the AlterLab Academic Skills suite.
Covers geospatial science across remote sensing, GIS, spatial analysis, and machine learning for earth observation — satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), raster and DEM operations, spectral indices (NDVI/EVI/NDWI), spatial statistics, point cloud processing, network analysis, and cloud-native workflows (STAC, COG, Planetary Computer), with examples across Python, R, Julia, JavaScript, C++, Java, Go, and Rust. Use for remote sensing workflows, satellite/raster image classification, terrain/slope/hillshade analysis, spatial ML on earth-observation data, hydrological modeling, marine spatial analysis, or atmospheric science. For pure tabular vector work with no raster/EO aspect (plain GeoPandas sjoin, buffer, overlay, dissolve, choropleths) prefer the geopandas skill; for celestial-sphere astronomy coordinates (ICRS/galactic, FITS, WCS) prefer the astropy skill. Part of the AlterLab Academic Skills suite.
Queries the OFR (Office of Financial Research) Hedge Fund Monitor API for time series on hedge fund size, leverage, counterparties, liquidity, complexity, and risk management, including SEC Form PF aggregated statistics, CFTC Traders in Financial Futures, FICC Sponsored Repo volumes, and FRB SCOOS dealer financing terms (no API key or registration required). Use when working with hedge fund data, systemic risk monitoring, financial stability research, hedge fund leverage or leverage ratios, counterparty concentration, Form PF statistics, repo market data, or OFR financial research data. Part of the AlterLab Academic Skills suite.
Extract and preprocess tiles from whole-slide images (WSI) with histolab — OpenSlide-backed slide loading, tissue detection and masks, Random/Grid/Score tile extraction, and image/morphological filters for H&E preprocessing. Use when the user needs lightweight WSI slide preprocessing — building tile datasets for ML training, tissue segmentation, or quick tile-based inspection of histopathology slides. For end-to-end computational-pathology, deep-learning model training, nucleus segmentation, or multiplexed/spatial-proteomics (CODEX, Vectra) pipelines prefer alterlab-pathml instead. Part of the AlterLab Academic Skills suite.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.
