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Register MCP features and serialize JSON-RPC requests into response data.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "MCP Serializer" yet — see the docs or source repo.
Register the following capabilities for an MCP service: tool get_weather, prompt template summarize_text, and resource docs://api-guide, then return a valid registration result structure.
Standardized registration data containing tool, prompt template, and resource definitions.
Serialize this JSON-RPC request into response data: {"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"get_weather","arguments":{"city":"Shanghai"}}}, and show the output structure.Protocol-compliant response data with the request ID, result fields, and serialized content.
Based on the following feature description, organize an MCP service interface catalog, separate tools, prompts, and resources, and provide serializable invocation examples.
A clear MCP capability catalog with invocation examples and data structures for each interface type.
Demo MCP server for calculations, time checks, notes, and code review prompts.
Turn any JSON-RPC handler into a production-ready MCP HTTP endpoint.
Quickly integrate and test MCP features with demo tools and resources.
Convert REST APIs into MCP tools for direct AI client access.
Connect to the mcp API via MCP to extend AI tool capabilities.
Convert any OpenAPI v3 spec into a working MCP server for AI integration.