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
This skill configures @data-client/endpoint to wrap custom async functions for non-REST/GraphQL patterns with Data Client hooks.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill installs and configures the appropriate data-client package for your project type and protocol, then delegates to protocol-specific setup.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you extract actionable insights from messy datasets by running analysis, cleaning data, and generating charts and reports automatically.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you design and optimize scalable data pipelines, warehouses, and analytics infrastructure across batch, streaming, and ELT workflows.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you drive data-driven feature development by guiding analysis, experimentation, and instrumentation across teams.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill routes uploaded files by type to specialized processors for data-analysis, data-viz, or data-base, enabling seamless delegation.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill analyzes network traffic patterns and validates stream integrity within the Teneo ecosystem to ensure reliable data flow.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill reviews code for database best practices, suggests improvements, and explains choices to improve performance, security, and scalability.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Model Context Protocol (MCP) server for Databricks that empowers AI agents to autonomously interact with Unity Catalog metadata. Enables data discovery, lineage analysis, and intelligent SQL execution. Agents explore catalogs/schemas/tables, understand relationships, discover notebooks/jobs, and execute queries - greatly reducing ad-hoc query time.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you configure Databricks CI/CD with GitHub Actions and Asset Bundles to streamline automated testing and deployments.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you set up a fast, reproducible Databricks local development loop with dbx, connect, and IDE integrations.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides Databricks production deployment with a complete checklist, governance, and rollback steps to ensure a safe go-live.
- 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.