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MCP & Tool Integration
MCP servers, tool-use layers, SDK adapters, and integrations that connect agents to external tools.
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
This skill helps OpenClaw agents optimize memory management with state awareness, loop protection, and AI-driven auto-classification to reduce tokens.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Explore any codebase from scratch and generate six quality artifacts: a quality constitution (QUALITY.md), spec-traced functional tests, a code review protocol…
- Fit
- 61 / 100
- Trust
- Verified source
- Install
- MCP ready
Review links
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Run Quantum ESPRESSO DFT calculations. Use when asked to perform first-principles calculations, SCF, structural relaxation, band structure, DOS, phonons, or any ab initio quantum mechanical calculation.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Writes and executes SQL queries from simple SELECTs to complex multi-table JOINs, aggregations, and subqueries. Use when the user asks to query a database,…
- Fit
- 61 / 100
- Trust
- Verified source
- Install
- MCP ready
Review links
Orchestrate multiple AI agents to gather insights, take action, and earn rewards autonomously.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill enables agents to read on-chain data across Base, Ethereum, Polygon, Solana, and Unichain via Quicknode RPC with optional x402 payments.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Qwen-Agent: Enhancing LLMs with Agent Workflows, RAG, Function Calling, and Code Interpreter.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Build Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill helps you compare and choose retrieval augmented generation frameworks like LangChain, LlamaIndex, and Sentence Transformers for document QA.
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
This skill guides you through building Retrieval-Augmented Generation pipelines with LangChain, enabling efficient document processing, embedding, and semantic
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
- Fit
- 61 / 100
- Trust
- Needs review
- Install
- MCP ready
Review links
Review links
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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.