Install payload
Install payload is mixed and needs spot-checking.
67% (8/12)
5 trusted · 92 review · 1 limited in this set — compare to see which signals differ.
Trust signals across 40 of 98 results
2 trust signals differ in this sample: Source provenance, Submitter
Signals differ on Source provenance, Submitter — add entries to compare before you install.
Rollout signal scan
Biggest gaps: metadata review, package integrity. 0 entries have 2+ required gaps.
Install payload
Install payload is mixed and needs spot-checking.
67% (8/12)
Most at-risk entries in this view
Adoption queue
21/98 visible results are in hold tier and need mitigation before adoption.
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/ai-search-ranking-content-cluster-strategy · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
mcp/box-mcp-server · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/cloudflare-workers-ai-edge · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/cloudflare-workers-d1-kv-r2-capability-pack · trust trusted · confidence 83%
1 blockers: Metadata review
70/100
Request metadata review from maintainers or internal owners.
skills/supabase-realtime-database · trust trusted · confidence 83%
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
skills/dotnet-agent-skills · trust review · confidence 67%
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
commands/cloudflare-deploy-readiness · trust review · confidence 67%
1 blockers: Metadata review
50/100
Request metadata review from maintainers or internal owners.
Collect package checksum or signed artifact information.
commands/test-advanced · trust review · confidence 67%
Decision confidence
20/98 results are low-confidence and need review before adoption.
Confident candidate for staged adoption.
74/100
skills/ai-search-ranking-content-cluster-strategy · trust trusted
Confident candidate for staged adoption.
74/100
mcp/box-mcp-server · trust trusted
Confident candidate for staged adoption.
74/100
skills/cloudflare-workers-ai-edge · trust trusted
Confident candidate for staged adoption.
74/100
skills/cloudflare-workers-d1-kv-r2-capability-pack · trust trusted
Confident candidate for staged adoption.
74/100
skills/supabase-realtime-database · trust trusted
Address Metadata review, Package integrity before broader rollout.
54/100
skills/dotnet-agent-skills · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
commands/cloudflare-deploy-readiness · trust review
Address Metadata review, Package integrity before broader rollout.
54/100
commands/test-advanced · trust review
Freshness distribution
Median age 40 days; all 12 scanned entries are within 90 days.
Theme distribution
100% of this view shares the top theme. Leading themes: rag, mcp, ai-agents.
81 distinct themes across 24 scanned
Open-source RAG and agentic retrieval platform with DeepDoc document understanding, visual chunking, grounded citations, heterogeneous data-source ingestion, agent workflows, MCP support, code executor support, and Docker self-hosting.
Connect Claude to a running RAGFlow deployment through its built-in MCP server, so agents can retrieve grounded chunks from selected datasets using RAGFlow's DeepDoc-powered retrieval pipeline.
Open-source evaluation framework for testing RAG systems, prompts, agents, workflows, and other LLM application behavior.
Open-source all-in-one AI framework for semantic search, LLM orchestration, and language-model workflows, built around an embeddings database that unions sparse and dense vector indexes, graph networks, and relational databases, with pipelines, workflows, agents, and web and MCP APIs.
Open-source, LLM-friendly Python web crawler and scraper that turns web pages into clean, LLM-ready Markdown for RAG, agents, and data pipelines, with an async browser pool, caching, structured extraction, and adaptive deep crawling.
Modular open-source Python framework for building AI agents and LLM workflows with structures, tools, memory, drivers, and RAG engines, from Griptape.
Open-source Python AgentOS and multi-agent framework, evolved from AutoGen, for building conversable agents, group chats, swarms, human-in-the-loop workflows, tool use, RAG, code execution, and provider-backed agent systems.
Local-first AI application for private chat, document RAG, workspace agents, MCP-compatible tools, model routing, memories, scheduled tasks, multimodal workflows, multi-user Docker deployments, and self-hosted agent automation.
Open-source Python multi-agent framework for building agent societies, role-playing agents, stateful ChatAgent workflows, RAG agents, synthetic data generation, MCP-enabled use cases, and research-scale agent experiments.
Production-ready LLM app and agentic workflow platform with visual workflows, RAG pipelines, agent capabilities, model management, observability, prompt IDE, APIs, Dify Cloud, and self-hosted Docker Compose deployment.
Visual low-code builder for AI agents, RAG apps, chatbots, agentic workflows, multi-agent systems, LangChain-based components, API-serving flows, and self-hosted deployments through npm, Docker, and cloud platforms.
Open-source agent engineering framework for building LLM applications with agents, model abstractions, tools, middleware, RAG, streaming, memory, MCP adapters, LangGraph-backed execution, and LangSmith observability hooks.
Idiomatic Java/JVM library for building LLM-powered applications with unified model APIs, tool calling, agentic workflows, RAG, chat memory, embedding stores, MCP client support, and Spring Boot, Quarkus, Helidon, and Micronaut integrations.
Official NVIDIA-verified Agent Skills catalog for AI agents working with CUDA-X, RAG Blueprint, NemoClaw and OpenClaw, NeMo, TAO, cuOpt, Omniverse, Physical AI, vision AI, simulation, robotics, and GPU workflows.
Self-hosted AI platform and web UI for Ollama, OpenAI-compatible APIs, RAG, Python function tools, model builder workflows, artifacts, web search, vector databases, enterprise auth, observability, plugins, and MCP-adjacent OpenAPI integrations.
Open-source Qwen agent framework for building LLM applications with function calling, tools, planning, memory, RAG, MCP support, Docker-based code interpreter, Gradio GUI demos, BrowserQwen, Custom Assistant, and Qwen Chat backend usage.
Query your Vectara RAG corpora from Claude — ask grounded questions with full answer generation, run semantic search to retrieve ranked document chunks, and detect and correct hallucinations using Vectara's Hallucination Correction API — with the official Vectara MCP server.
Open-source TypeScript agent engineering framework and platform for building AI agents with tools, memory, workflows, RAG, guardrails, evals, MCP, voice, and VoltOps observability.
Official Agentset MCP server that lets Claude retrieve cited knowledge-base results from an Agentset namespace through the `knowledge-base-retrieve` tool, with optional tenant scoping and custom tool descriptions.
MCP server for the Graphlit platform, enabling Claude to ingest, search, retrieve, organize, and operate on files, web pages, feeds, collections, conversations, memory, connectors, crawls, and RAG-ready project knowledge.
Open-source AI orchestration framework for building production-ready agents, RAG pipelines, multimodal search, retrieval, and tool-using LLM applications.
Open-source framework for building agentic LLM applications over private data with ingestion, indexes, retrieval, RAG, tools, workflows, and evaluation.
Apache-2.0 vector database for scalable ANN search, hybrid retrieval, RAG, recommendation systems, image search, multimodal search, and AI agent memory.
Open-source, cloud-native vector database for semantic search, hybrid search, RAG, reranking, multimodal retrieval, agent workflows, and production AI applications.
The official Codacy MCP server (@codacy/codacy-mcp) that gives AI assistants access to the Codacy API for code quality, security, and coverage — listing repository and pull-request issues, retrieving file coverage and duplication, searching security (SRM) findings, inspecting analysis tools and patterns, and running local analysis with the Codacy CLI.
Framework-agnostic agent memory lifecycle skill and Rust-native CLI for explicit recall, evidence-backed memory, forgetting, audit, consolidation, DOX/Revolve sync, and local SQLite/FTS storage.
Connect Claude to the full Appwrite backend platform — databases, authentication, serverless functions, teams, messaging, and storage — with the official Appwrite MCP server using dynamic dispatch across the entire Appwrite API surface.
Official Dart team Agent Skills for AI coding agents working on Dart unit tests, CLI apps, coverage, runtime errors, mocks, package conflicts, static analysis, Native Assets, FFI, ffigen, and pattern matching.
Microsoft open-source course for learning AI agents with lessons on agentic frameworks, design patterns, tool use, agentic RAG, trustworthy agents, planning, multi-agent systems, MCP/A2A/NLWeb, memory, browser use, and Microsoft Agent Framework.
Expert MCP OAuth server hardening capability pack applying documented Dynamic Client Registration, oauth.scopes pins, callback ports, keychain token storage, and least-privilege scope review from official MCP documentation.