Die Werkzeugbeschreibungen sind auf Englisch.

RAG und Suche

Retrieval, Vektordatenbanken, Embeddings und semantische Suche.

Anwendungsfall

Aktivität

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147

Werkzeug-Rangliste

Gemischte Rangfolge: Gemessenes Wachstum hat Vorrang. Rohwerte behalten ihr eigenes Zeitfenster; eine Änderung erfordert mindestens zwei Messungen in 7 Tagen.

  1. 1

    Agent
    Aufgegeben

    Open-Source AI-powered web browser. Browse the web with your own LLM API key. Alternative to Dia / Comet.

    githubgemessenes WachstumQuelle öffnen ↗

    94GitHub-Sternestabil
  2. 2

    MCP
    Aktiv

    Cross-platform persistent memory MCP for Codex, Gemini CLI, Claude Code, and other local MCP hosts. 36 cited neuroscience mechanisms, local-first SQLite/PostgreSQL, hybrid retrieval, decay-based consolidation, and reproducible benchmarks.…

    githubgemessenes WachstumQuelle öffnen ↗

    71GitHub-Sternestabil
  3. 3
    Aktiv

    Semantic Scholar API wrapper for agents — search 200M+ papers, traverse citations, find authors. Python, rate-limited, multi-agent.

    githubgemessenes WachstumQuelle öffnen ↗

    Installieren git clone https://github.com/Agents365-ai/semanticscholar-skill ~/.claude/skills/semanticscholar-skill

    68GitHub-Sternestabil
  4. 4
    Aktiv

    The official Pinecone marketplace for Claude Code Plugins

    githubgemessenes WachstumQuelle öffnen ↗

    Installieren /plugin marketplace add pinecone-io/pinecone-claude-code-plugin

    68GitHub-Sternestabil
  5. 5
    Aktiv

    Token-efficient code review knowledge graph: semantic search and call-graph resolution.

    mcpgemessenes WachstumQuelle öffnen ↗

    Installieren claude mcp add better-code-review-graph -- uvx better-code-review-graph

    66GitHub-Sternestabil
  6. 6
    Aktiv

    Persistent memory for Claude Code & Codex CLI. Auto-extracted knowledge graph, multi-representation embeddings, 3D WebGL visualization. LongMemEval R@5=97.45%. Self-hosted, Ollama-optional

    githubgemessenes WachstumQuelle öffnen ↗

    66GitHub-Sternestabil
  7. 7
    Aktiv

    RuvNet Brain — a downloadable, source-grounded brain for Claude Code over Reuven Cohen's (rUv's) RuvNet stack: RuVector/RVF, Ruflo, AgentDB, RuLake, SPARC + 21 building blocks. Grounds Claude in real source via one MCP tool (search_ruvnet),…

    githubgemessenes WachstumQuelle öffnen ↗

    64GitHub-Sternestabil
  8. 8
    Aktiv

    Agent skills for LandingAI's Agentic Document Extraction (ADE) — production-ready document AI for agentic coding assistants

    githubgemessenes WachstumQuelle öffnen ↗

    Installieren git clone https://github.com/landing-ai/ade-document-processing-skills ~/.claude/skills/ade-document-processing-skills

    64GitHub-Sternestabil
  9. 9

    Agent
    Aktiv

    Vane is an AI-powered answering engine.

    githubgeschätztes MomentumQuelle öffnen ↗

    36 578GitHub-Sterne

Lern- und Referenzressourcen

Nach gemessenem Wachstum und quellenübergreifend normalisiert sortiert. Diese Ressourcen bleiben getrennt zugänglich und fließen nicht in die Hauptwertung ein.

  1. 1
    RuhendQuelle öffnen ↗

    A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.

    github

    Installieren git clone https://github.com/BennettSchwartz/membrane ~/.claude/skills/membrane

    Ressourcegemessenes Wachstum
    94GitHub-Sternestabil
  2. 2
    AktivQuelle öffnen ↗

    Build LLM systems you actually control. A free, open engineering book + course — from tokenization to serving your own models. Mechanisms, trade-offs, and numbers, not prompt tips

    githubRessourcegemessenes Wachstum
    46GitHub-Sternestabil
  3. 3
    AktivQuelle öffnen ↗

    Official Claude Documentation - Converted to 2000+ Markdown Files - All documentation sourced from first party sources- 24 categories - refreshed daily, multi-agent orchestration

    github

    Installieren /plugin marketplace add johnzfitch/claude-wiki

    Ressourcegemessenes Wachstum
    21GitHub-Sternestabil
  4. 4
    AktivQuelle öffnen ↗

    My complete journey to becoming an Agentic AI Engineer through structured learning, projects, experiments, and production-ready implementations of modern AI systems.

    githubRessourcegemessenes Wachstum
    18GitHub-Sternestabil
  5. 5
    RuhendQuelle öffnen ↗

    Persistent memory for Claude Code. Auto-capture decisions, learnings, client info. Cloud backup to Supabase. Never lose context again. Free alternative to Mem.ai, Rewind AI, Personal AI.

    githubRessourcegemessenes Wachstum
    14GitHub-Sternestabil
  6. 6
    AktivQuelle öffnen ↗

    Spring AI 实战教程 🚀 ChatClient → RAG → MCP → Agent → A2A,24 个手写模块循序渐进(Spring Boot 4.1 + Spring AI 2.0 + Java 21)

    githubRessourcegemessenes Wachstum
    3GitHub-Sternestabil
  7. 7
    RuhendQuelle öffnen ↗

    Collection of some interesting Generative AI usecases implementation.

    githubRessourcegemessenes Wachstum
    2GitHub-Sternestabil
  8. 8
    AktivQuelle öffnen ↗

    Curated Agentic AI resources: AI agent frameworks, tutorials, courses, projects, MCP tools, research papers, evaluation, security, and production guides.

    githubRessourcegemessenes Wachstum
    2GitHub-Sternestabil
  9. 9

    ai-resources

    Sonstige
    AktivQuelle öffnen ↗

    Comprehensive collection of AI concepts, research findings, and practical implementations. From machine learning fundamentals to cutting-edge LLMs, agents, and emerging technologies.

    githubRessourcegemessenes Wachstum
    1GitHub-Sternestabil
  10. 10
    AktivQuelle öffnen ↗

    Detect underpriced products by scraping deals and using AI models to estimate fair prices for profit opportunity identification.

    githubRessourcegemessenes Wachstum
    1GitHub-Sternestabil
  11. 11
    AktivQuelle öffnen ↗

    Handbook técnico aberto sobre engenharia de IA em produção: ML tradicional, LLMs, RAG, agentes, segurança, observabilidade, FinOps e deployment.

    githubRessourcegemessenes Wachstum
    1GitHub-Sternestabil
  12. 12
    RuhendQuelle öffnen ↗

    Interactive roadmap for becoming an Agentic AI Engineer — 11 stages from Python & FastAPI to multi-agent systems, MCP, RAG, Docker, and context engineering

    githubRessourcegemessenes Wachstum
    1GitHub-Sternestabil
  13. 13
    RuhendQuelle öffnen ↗

    50+ AI agent apps you can actually run — MCP, A2A, LangGraph, SAP, RAG, and multi-agent patterns

    githubRessourcegemessenes Wachstum
    0GitHub-Sternestabil