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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
305page
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
playbooks / skill
langchain-reference-architecture skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps design production-ready LangChain architectures with scalable patterns, provider abstraction, and chain management for enterprise LLM
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-security-basics skill by jeremylongshore/claude-code-plugins-plus-skills
This skill helps you implement LangChain security best practices from secrets management to prompt protection for safe production usage.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-tools skill by a5c-ai/babysitter
This skill helps you create and integrate LangChain tools with robust schemas, enabling reliable function calling and resilient tool orchestration.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-use-skill skill by nanmicoder/claude-code-skills
This skill provides a concise LangChain 1.0 quick reference for building agents, tools, memory, and middleware workflows.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain-workflow-builder skill by patricio0312rev/skills
Builds LLM applications with LangChain including chains, agents, memory, tools, and RAG pipelines. Use when users request "LangChain setup", "LLM chain", "AI workflow", "conversational AI", or "RAG pipeline".
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain4j-ai-services-patterns skill by giuseppe-trisciuoglio/developer-kit
This skill helps you build declarative, type-safe AI services with LangChain4j in Java, enabling memory, tool integration, and structured outputs.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / skill
langchain4j-rag-implementation-patterns
Complete Retrieval-Augmented Generation systems with LangChain4j for knowledge-enhanced AI applications. \n \n Document ingestion pipelines with configurable…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain4j-rag-implementation-patterns skill by giuseppe-trisciuoglio/developer-kit
This skill helps you implement Retrieval-Augmented Generation patterns with LangChain4j to build knowledge-rich QA and document-aware assistants.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain4j-spring-boot-integration skill by giuseppe-trisciuoglio/developer-kit
This skill helps Spring Boot developers integrate LangChain4j with declarative AI services and auto-configuration for production-grade AI apps.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / skill
langchain4j-testing-strategies
Comprehensive testing strategies for LangChain4j applications with mocks, containers, and RAG validation. \n \n Provides unit testing patterns with mock mode…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
playbooks / skill
langchain4j-testing-strategies skill by giuseppe-trisciuoglio/developer-kit
This skill provides testing strategies for LangChain4J applications, enabling reliable unit, integration, and end-to-end tests with mocks and Testcontainers.
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
explainx / skill
langchain4j-tool-function-calling-patterns
Annotation-based and programmatic tool system for LangChain4j agents to execute external functions, APIs, and services. \n \n Define tools using @Tool annota…
MCPHTTPCLI
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review support
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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.