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Build MCP servers, which expose tools and data to AI agents, with mcp-use. The material covers server functions, reusable prompts, and interactive React widgets, but this skill is deprecated and points to mcp-app-builder as its replacement.
A deprecated guide to building MCP servers with mcp-use, covering callable actions, data resources, reusable prompts, and interactive widgets. It includes design references and code examples, and directs users to the replacement skill, mcp-app-builder.
Work directly with MCP servers, which connect AI agents to external tools. List available tools, inspect their inputs, manage configuration and authentication, and call them through HTTP or local process connections using mcporter.
Build MCP servers that let AI access actions and data using mcp-use. The guide covers project setup, reusable prompts, interactive React interfaces, authentication, error handling, and deployment, with reference files for each area.
Package a local MCP server, which connects an AI host to tools, as a .mcpb file. Include dependencies and runtime support, define installation settings, and validate, test, and sign the bundle for distribution.
Guides development of MCP servers that let AI access external actions and data using mcp-use. Covers project setup, tools, reusable prompts, interactive React interfaces, authentication, validation, and deployment through task-specific reference guides.
Build and maintain TypeScript MCP servers that connect AI to tools, plus interactive MCP Apps, using mcp-use. The skill guides implementation, authentication, migration, and verification based on the package version and types installed in the project.
Build and maintain TypeScript MCP servers that connect AI to tools, plus interactive MCP Apps, using mcp-use. The skill guides implementation, authentication, migration, and verification based on the package version and types installed in the project.
Guides development of ChatGPT apps with interactive widgets using mcp-use and OpenAI Apps SDK, covering server tools, React interfaces, and shared state. This skill is deprecated and directs users to mcp-app-builder.
Build and maintain TypeScript MCP servers and MCP Apps with mcp-use, giving AI assistants tools and interactive views. Guides implementation, authentication, debugging, migration, review, and verification against the package version installed in the project.
Review MCP configurations for exposed credentials, risky command patterns, and package versions that can change unexpectedly. Produce a report with severity levels and suggested fixes without running the commands defined in the configuration.
Build and troubleshoot C#/.NET MCP servers that expose tools and information to AI agents. Guidance targets the official 2.x SDK and covers transport setup, authentication, interactive features, basic clients, and migration issues caused by changed defaults.
Review MCP configuration without running its servers. Identify npm, Python, and Docker references that may fetch different code later, classify their version settings, and recommend pinning versions or image contents that the team has reviewed.
Turn an OpenAPI or Swagger specification into an MCP server, a bridge that lets AI assistants call an API. Covers tool generation, authentication, local testing, and deployment to mcp-use cloud.
Connect external services to Claude Code plugins through MCP, a protocol that exposes service functions as tools. Get guidance on server configuration, connection methods, authentication, tool permissions, and testing connections and tool calls.
Audit MCP servers, which provide external tools to AI agents, for hidden instructions, changes after approval, unsafe internal requests, and missing authentication. Use mcp-scan and manual checks to document risks and recommended fixes.
Build MCP servers, connectors that let AI models use external services through tools. This skill guides API research, tool design, implementation in TypeScript or Python, testing, and evaluation with realistic questions that require multiple tool calls.
Configure MCP connections, which link AI agents to tools, for AWS documentation search and API access. Check existing settings, choose between documentation-only and full API access, verify available tools, and troubleshoot connection or credential problems.
Plan and build an MCP server, a connection that lets Claude use external tools. Choose hosting, tool structure, authentication, and a framework, then scaffold a server or hand off to specialized packaging and interface skills.
Build remote MCP servers, which let AI agents call external tools, on Cloudflare Workers. This skill covers server code, tool definitions, OAuth authentication, local testing, deployment, and connecting a Codex client.
Build MCP servers, which give AI agents tools for external services, using Python or TypeScript. The skill guides tool design, input validation, error handling, code review, and evaluations based on realistic tasks.
Review source code for MCP, a protocol connecting AI applications to tools. Check authentication, input validation, unsafe execution, and other security risks, then report findings with file and line references and separate manual follow-ups.
Plan how an AI agent should interact with Zoom through MCP, a protocol for calling tools. Assess task suitability, divide responsibilities between MCP and REST APIs, and identify connection, authentication, and client requirements.
Build MCP servers, which give AI agents tools for external services, using Python or TypeScript. The skill guides tool design, input validation, error handling, code review, and evaluations based on realistic tasks.