Find, trial, compare, and govern AI agents before hiring
Multi-agent Orchestration
Frameworks and tools for coordinating multiple agents, teams, roles, swarms, or AI workforces.
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Coordinate several agents around one outcome.
- Assign specialist roles and handoffs.
- Inspect launch packets before running a team.
Recommended trials and bundles
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
This skill guides upgrading Databricks runtime, migrating to Unity Catalog, updating APIs, and upgrading Delta Lake with validation and automation.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Production-ready Dataverse SDK patterns with error handling, batch operations, and optimization techniques. \n \n Demonstrates exponential backoff retry logi…
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you manage Volcengine TOS storage tasks efficiently by performing bucket and object operations with validation and logging.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill provides guidance on clean architecture, outlining layer separation, dependency rules, and architectural patterns to structure robust applications.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you search the web using DuckDuckGo Lite when no API key is available, returning titles, URLs, and snippets.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you build cross-chain Solana to EVM bridges using deBridge, enabling fast token transfers and message passing.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you diagnose and fix Firebase emulator issues, rules violations, and deployment failures with a structured troubleshooting workflow.
- Fit
- 66 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides rigorous, evidence-based debugging of complex issues, prioritizing root-cause analysis over quick fixes.
- Fit
- 66 / 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.
4955 matching candidates for Multi-agent Orchestration. 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.