Find, trial, compare, and govern AI agents before hiring
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
Enables AI assistants to interact with Kubernetes clusters using natural language. Browse Kubectl MCP Server for Claude, Cursor, VS Code, and other AI agents.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides building a Python gRPC key-value store from proto to server and verification, ensuring reliable, testable APIs.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
A local-first tool that performs read-only audits of applications built with AI. It produces an evidence-based 0-100 production readiness score and provides guided fixes along with a learning plan. Includes a dashboard, CLI, and MCP for workflow integration.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct…
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
ALWAYS START HERE for any LangChain, Deep Agents, or LangGraph open source agent project. It is the required starting point for any LangChain open source agent…
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you build and deploy LLM-powered apps using LangChain components, RAG, and memory with practical code examples.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you build and orchestrate LangChain and LangGraph workflows for RAG pipelines, agents, and complex LLM chains.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
Technical category pages stay focused on job browsing; complete review records and finalist profile resources stay linked here.
Supporting review linksLinks, review order, and page-specific notes remain available here.
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.