432 AI tools for Research & summarize
Research Assistant bundle combines MCP servers (Brave Search, Firecrawl, Notion, Memory), agents, and prompts for research workflows across web sources, with
Complete B2B persona research kit that generates structured reports with workflows, pain points, costs, and sourced quotes using Tavily and Bright Data MCP
Autonomous agent synthesizes user feedback from multiple sources into prioritized product direction and actionable development recommendations.
Autonomous Legal Compliance Checker reviews documents and practices to ensure regulatory adherence, identify risks, and provide actionable recommendations.
Build thriving Reddit communities with an autonomous agent that researches, strategizes, and executes growth plans.
Autonomous Tool Evaluator agent for in-depth development tool and framework comparisons, benchmarks, and recommendations.
Autonomous UX researcher agent that follows a structured process to analyze user feedback and analytics, producing evidence-based reports with personas
Agentic RAG implements retrieval agents for decision-making on index retrieval, powered by LangGraph.
Autonomous trend researcher identifies emerging trends, viral patterns, and market opportunities across platforms for actionable insights.
Conduct comprehensive market research and analysis for strategic decision-making. Identifies market size, trends, segments, growth, barriers, and opportunities.
Analyze competitors' websites, features, pricing, content, and social presence to inform marketing and sales strategies.
Compensation benchmarking agent for market analysis, pay equity, and compensation structure development.
Build detailed competitive analysis grids using the PACE framework, identifying market opportunities and strategic advantages for informed business decisions.
AI design critique agent providing structured, actionable feedback on UX, visual design, and accessibility using established frameworks.
Generate and optimize text embeddings for semantic search and ML applications. Supports batch processing and advanced chunking.
Expert agent that designs scientifically-backed employee engagement surveys using validated frameworks (Gallup Q12, UWES), analyzes results with statistical
Framework for implementing SHAP, LIME, permutation importance, partial dependence, and counterfactual explanations.
Create comprehensive lessons learned documentation templates for project insights and continuous improvement.
Design and implement robust LLM assessment frameworks for accuracy, safety, and alignment.
A VibeBaza skill file that provides Claude with a structured prompt for creating risk-mitigation plans.
Access arXiv LaTeX source with AI clients like Claude and Cursor for accurate math and equation processing.
Basic Memory MCP Server: Connect AI clients to your knowledge base for persistent context and semantic search. Free local install or $15/mo cloud.
AI Context Engineering for Large Repositories. Transforms codebases into searchable, AI-consumable knowledge with 5:1 compression.
MCP server providing AI models with search, BibTeX generation, and bibliographic analysis tools for the DBLP computer science publication database.
Google Scholar MCP Server provides Google Scholar search capabilities through a streamable HTTP transport.
MCP server that searches documents using Google Vertex AI with Gemini grounding, supporting multiple data stores and stdio/SSE transports.
Access 3M+ SaaS reviews, pricing, and feature data via MCP endpoint.
MCP server that converts HTML webpages to clean Markdown with 90-95% size reduction, preserving tables and images, with Playwright support for JavaScript-heavy
TypeScript MCP server providing local-first document management with embedded Orama vector database, hybrid search, parent-child chunking, and built-in web
A collection of system prompts from CAMEL-AI designed to explore and test AI assistant misalignment behaviors for research and safety evaluation purposes.
Persona Hub Prompts from CAMEL-AI provides system prompts that define assistant behavior and role characteristics for conversational AI applications.
A Semantic Kernel prompt template that extracts entities related to a specified topic from input text and returns both the entities and source text.
A prompt that checks whether entities in a list are grounded in a reference context, returning unsupported items as a bulleted list.
Solution Extraction prompts from CAMEL-AI that guide AI assistants to systematically extract, structure, and present solutions from complex problem-solving
System prompt template from CAMEL-AI that configures AI assistants to perform object recognition tasks in images and visual data.
Adaptive RAG strategy that unites query analysis with self-corrective RAG.
Adaptive RAG with Cohere Command R, routing across web search, iterative RAG, or LLM answers for efficient information retrieval.
LangGraph workflow routing RAG queries between web search and self-corrective retrieval using Mistral/Mixtral models via Ollama and Nomic embeddings.
Corrective RAG (CRAG) is a LangGraph workflow that self-grades retrieved documents for relevance and supplements poor results with web search to improve answer
Implement Corrective RAG (CRAG) with local LLMs and Tavily Search.
Self-RAG enhances RAG with self-reflection and grading for retrieved documents and generations.
Self-RAG workflow using LangGraph that grades retrieved documents and generations for relevance, hallucination detection, and response quality, based on the
A chatbot prompt workflow that maintains conversation history to generate contextually aware responses in multi-turn Wikipedia-based interactions.
Automate the evaluation of Q&A systems by using LLMs to measure response quality and safety, achieving high agreement with human assessments.
