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Roles / Technical Category
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Multi-agent Orchestration
Frameworks and tools for coordinating multiple agents, teams, roles, swarms, or AI workforces.
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4955filtered
299page
413pages
Category fit
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
playbooks / skill
kv-store-grpc skill by letta-ai/skills
This skill guides building a Python gRPC key-value store from proto to server and verification, ensuring reliable, testable APIs.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
enterprisedna / tool
KyaniteLabs/checkyourself
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.
MCPCLISDK
- 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
mcpservers / skill
langchain
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
mcpservers / skill
LangChain Agent Starter Kit
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…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain skill by bobmatnyc/claude-mpm-skills
This skill helps you build and deploy LLM-powered apps using LangChain components, RAG, and memory with practical code examples.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain skill by hoodini/ai-agents-skills
This skill helps you build and orchestrate LangChain and LangGraph workflows for RAG pipelines, agents, and complex LLM chains.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain skill by orchestra-research/ai-research-skills
This skill helps you rapidly build LLM applications using agents, chains, and RAG with multi-provider support and robust tooling.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain skill by vamseeachanta/workspace-hub
Build production-ready LLM applications with chains, agents, memory, tools, and RAG pipelines using the LangChain framework
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain_patterns skill by vuralserhat86/antigravity-agentic-skills
Implement Retrieval-Augmented Generation (RAG) systems with LangChain4j. Build document ingestion pipelines, embedding stores, vector search strategies, and knowledge-enhanced AI applications. Use when creating question-answering systems over document collections or AI assistants with external knowledge bases.
MCPHTTPCLI
- 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
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.
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.