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Build MCP-based AI-interactive servers with tools, resources, and flexible transports.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "bare-mcp" yet — see the docs or source repo.
Using bare-mcp, create a minimal runnable MCP server example for Node.js with a calculator tool and a static resource endpoint, and explain how to run it locally.
Provides runnable server code, dependency notes, and local startup steps.
Show how to use bare-mcp to configure both stdio and HTTP transports for one MCP server, and compare when each should be used.
Returns sample code for multiple transports plus a comparison of usage scenarios.
Using bare-mcp, design a tool interface callable by an LLM named fetch_project_status, taking a project ID and returning a project status summary, then generate the server code skeleton.
Outputs the tool definition, input/output schema, and server skeleton code.
Connect to the mcp API via MCP to extend AI tool capabilities.
Build MCP servers quickly to expose app data and actions to AI clients.
Capture project decisions and constraints during AI chats for seamless re-entry.
Build TypeScript MCP servers faster with a production-ready starter architecture.
Build, test, and deploy MCP servers for serverless and edge environments.
Build, debug, and manage software tasks with natural language across LLMs.