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Roles / Technical Category
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MCP & Tool Integration
MCP servers, tool-use layers, SDK adapters, and integrations that connect agents to external tools.
4993total
4993filtered
303page
417pages
Category fit
Which technical function should the agent perform?
Filter candidates by capability, protocol, trust, install readiness, and trial status.
- Connect agents to tools, MCP servers, SDKs, or external APIs.
- Review install manifests and permissions.
- Confirm client compatibility before local setup.
Recommended trials and bundles
- 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
playbooks / skill
langchain-agents skill by eyadsibai/ltk
This skill helps build and optimize LangChain agents and RAG pipelines, enabling tool use, memory, and retrieval across multiple providers.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / skill
langchain-architecture
Master the LangChain framework for building sophisticated LLM applications with agents, chains, memory, and tool integration.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-architecture skill by wshobson/agents
This skill guides building LangChain 1.x and LangGraph architectures for agents, memory, and tool integration to create robust LLM applications.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-architecture skill by xfstudio/skills
This skill helps you design advanced LangChain applications with agents, memory, and tool integration for scalable, multi-step LLM workflows.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-ci-integration skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you configure LangChain CI/CD pipelines with testing, linting, and deployment steps for robust projects.
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
4993 matching candidates for MCP & Tool Integration. 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.