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Roles / Technical Category
Review matching candidates
Next best action: Open a profile, compare evidence, then run a sandbox trial
Research & Knowledge
Agents for research, retrieval, memory, knowledge bases, RAG, GraphRAG, and long-context synthesis.
4677total
4677filtered
286page
390pages
Category fit
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
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / agent
LaVague
LaVague is an open-source framework designed for developers who want to create AI Web Agents to automate processes for their end users.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
lead-enrichment-pipeline skill by openclaw/skills
This skill automates lead capture, deduplication, scoring, and team notifications using n8n workflows and Google Sheets to accelerate follow-up.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
lead-research-assistant-cn skill by openclaw/skills
This skill helps you identify and qualify potential leads for your business by analyzing your product and providing actionable outreach strategies.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
lelamp-room skill by openclaw/skills
This skill enables agents to create or join a shared 3D lobster room, interact in real-time, and coordinate via IPC and Nostr relays.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
lemnos-cost-guard skill by openclaw/skills
This skill tracks API costs, detects context bloat, and enforces budgets for OpenClaw agents to optimize spending and routing.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / agent
Lemon Agent
Plan-Validate-Solve (PVS) Agent for accurate, reliable and reproducable workflow automation
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / tool
Letta MCP Server Railway Edition - snycfire-core/letta-mcp-server-railway
Cloud-optimized HTTP transport edition enabling cloud deployment of Letta-powered agents via streamable HTTP.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
letta-expert skill by willsigmon/sigstack
This skill helps you build AI agents with true long-term memory using Letta to remember, learn, and improve across sessions.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / agent
LevelFields
AI scans for events proven to impact stock prices, so you don't have to.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review support
Open Category guide
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.
Category guideTechnical role guideAgent inventoryResource mapReview guideAPI referenceSite contextSitemapProfile resources
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.
Review route: OpenAI review tools can start with openai.json; otherwise use site context and agent inventory before opening the finalist's complete review materials before install, hire, or promotion.