14,252 mods in this category, of every kind an agent can take. Each one carries what it costs per session, what the scan found, and whether it is the original.
Plugin Claude Code
Live, machine-readable AI ecosystem and regulated-domain data: AI news across 12+ sources, model pricing across providers, AI service status, security advisories (CVE/KEV/EPSS/OSV), SEC EDGAR filings, FDA regulatory data (FAERS, drug labels, recalls, MAUDE), and US energy indicators via EIA Open Data. 17 free MCP…
MCP server Claude CodeCodexCursor +2
MCP server for LynxPrompt — browse, search, and manage AI configuration blueprints. Runs locally from the lynxprompt-mcp npm package. Needs 2 environment variables to run.
MCP server Claude CodeCodexCursor +2
Centrality-aware GraphRAG retrieval planner — drop-in layer over any vector DB. Runs locally from the hubmesh Python package.
Skill Claude CodeCodex
Use this when someone asks to "search documents", "query RAG", "ingest file", "ingest PDF", "save web page", "add to knowledge base", or mentions document search, semantic search, vector search, or RAG operations. Covers score interpretation ( 0.5 skip), query tips, and ingestion guidance for querydocuments…
Skill Claude CodeCodex
Use Neo's MCP server as a toolset inside LangChain agents. Neo executes AI/ML workloads locally on the user's machine — files are written directly to their workspace, never to a remote server.
MCP server Claude CodeCodexCursor +2
PQS scores any prompt before the model runs. 8 dimensions. 5 frameworks. Pre-flight, not post-hoc. Runs locally from the pqs-mcp-server npm package. Needs 1 environment variable to run.
MCP server Claude CodeCodexCursor +2
Calypso multimodal RAG for grounded answers from docs, images, charts, and knowledge. Runs locally from the @calypsohq/multimodal-rag-mcp-server npm package. Needs 2 environment variables to run.
MCP server Claude CodeCodexCursor +2
Data validation that discovers rules from your data so you don't have to write them. Runs locally from the goldencheck Python package.
Plugin Claude Code
Bundles 1 skill, 1 MCP server · 34 tokens together
Smart JSON-to-TOON conversion with pragmatic auto-gating for LLM prompts.
MCP server Claude CodeCodexCursor +2
Score your specs before feeding them to an LLM. MCP server with radar chart visualization. Runs locally from the spec-score-mcp npm package.
MCP server Claude CodeCodexCursor +2
One API key for 6 AI models. Pay-per-use. MCP protocol support with web search. Remote server at smithery.ai.
MCP server Claude CodeCodexCursor +2
A powerful RAG (Retrieval-Augmented Generation) system built with LangChain, designed as an MCP server for Cursor, VS Code, and other AI assistants. Runs locally from the pinrag Python package. Needs 3 environment variables to run.
MCP server Claude CodeCodexCursor +2
30 GPU-powered AI services as MCP tools. LLM, image, video, audio, embeddings & more. Runs locally from the @gpu-bridge/mcp-server npm package. Needs 1 environment variable to run.
MCP server Claude CodeCodexCursor +2
Universal web scraper with LLM-ready markdown, RAG chunking, PDF/DOCX support. Runs locally from the thecrawler npm package.
MCP server Claude CodeCodexCursor +2
Semantic code retrieval engine with hybrid search, context expansion, and 40+ language support. Runs locally from the @chiway/contextweaver npm package.
Skill Claude CodeCodex
Toolbelt is a collaborative substrate over your data. Upload any document — entities and relationships extracted automatically, queryable immediately. Ask questions that span structured tables, documents, and relationships in a single call. No stitching databases together. Toolbelt orchestrates semantic, structured…
Skill Claude CodeCodex
Guides the user in discovering a better model structure (e.g. from feature transformations in logistic regression to equation terms within PDEs to neural network layer compositions) out of data. Use when the user asks to create or improve an existing model. Uses an iterative meta/inner agent loop to explore structural…
jiachengwang-punch/small-sample-analysis
Skill Claude CodeCodex
End-to-end methodology for supervised machine learning on small datasets (typically 30-200 samples) where standard "throw XGBoost at it" approaches fail. Use this skill whenever the user is building a predictive model on a small dataset, especially when sample-to-feature ratios are tight, when interpretability matters…
Skill Claude CodeCodex
Run differential expression analysis on bulk RNA-seq count data with DESeq2 (R). Covers DESeqDataSet construction from a count matrix, tximport (Salmon/Kallisto), featureCounts, or SummarizedExperiment; pre-filtering; design formulas (simple, batch, paired, interaction, multi-factor, LRT); result extraction by…
Skill Claude CodeCodex needs its repo
Import an Obsidian vault into ChromaDB for semantic search. Parses markdown files, extracts frontmatter, headings, tags, and content sections. Chunks intelligently by heading hierarchy. Use when indexing a knowledge base, importing notes for semantic recall, or syncing an Obsidian vault to a vector database.
mturac/recsys-pipeline-architect
Skill Claude CodeCodex
Designs composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by X's open-sourced For You algorithm. Use this skill when the user wants to build any system that picks "the top K items for a user/context" — content feeds…
gootf/corpus-knowledge-engineering
Skill Claude CodeCodex
Turn document corpora (books, merged TXT, PDF/EPUB, OCR text) into structured agent knowledge: normalize → deterministic source segmentation → chapter maps with provenance → book skills → evaluation gates. Use when the user wants to convert books/materials into AI skills, build a knowledge base from a corpus, evaluate…
Skill Claude CodeCodex
Spectral vector search using graph Laplacian eigenstructure. Build signal graphs, run λτ-indexed queries, and analyse spectral properties of vector datasets.
Skill Claude CodeCodex
Analyze prompts for constraint complexity, audit failure risks, and generate optimized rewrites for Claude and GPT. Based on "How LLMs Follow Instructions" (Rocchetti & Ferrara, 2026) constraint taxonomy research. Use when reviewing prompt files, optimizing prompt bases, or auditing instruction quality. Trigger…
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