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Research & Knowledge
Agents for research, retrieval, memory, knowledge bases, RAG, GraphRAG, and long-context synthesis.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Collect and synthesize source-backed research.
- Build reusable knowledge assets.
- Preserve citations and assumptions for review.
Recommended trials and bundles
This skill guides you using the Letta Conversations API to manage isolated conversation threads on a single agent for multi-user chat and testing.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you convert a web app into a hybrid MCP App, enabling seamless standalone and MCP-host rendering from a single codebase.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you connect to MCP servers and convert them into reusable tools, accelerating repeated integrations.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides you through initializing Convex agents, managing threads, and generating LLM responses for chat-based interactions.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Implement Convex authentication and authorization patterns with OIDC providers or Convex Auth. Use for auth provider setup, ctx.auth usage, user identity handling, and auth-aware schema patterns. Use proactively when users mention auth, JWT, Clerk/Auth0/WorkOS, or Convex Auth. Examples: - user: "Add auth to Convex" → choose provider and outline setup - user...
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps implement correlation IDs and distributed tracing across microservices to improve observability, debugging, and request-flow analysis.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you implement production-grade Azure Cosmos DB services in Python with clean architecture, dual authentication, and test-driven patterns.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Enables AI agents to interact with the Courier notification API, allowing them to send messages, manage profiles, debug deliveries, configure lists, and more through 60 tools.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill connects your AI agent to Hannah and Elena for marketing research and operational planning via API or email.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Scrape any URL with JavaScript rendering and get back clean markdown — built for AI agents, LLM pipelines, and autonomous research workflows.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides you through creating new browser automation scripts with the stagehand CLI to accelerate website tasks and data extraction.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides you from zero to fully register an OpenClaw Agent with questionnaire, workspace, CLI setup, and evolution-ready defaults.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
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4677 matching candidates for Research & Knowledge. Open candidate profiles for fit, setup guidance, trust evidence, and sandbox trial planning.
- 01Site contextShared review rules
- 02Role categoryOpen the focused review record
- 03Agent inventoryBrowse the matching inventory
- 04Profile resourcesEvidence, setup, trust, trial, and history files
Use the links and review path below for role-category candidates, related playbooks, and finalist profile resources before action.