What is the difference between synchronous and asynchronous clients?
`McpSyncClient` blocks on each call, while `McpAsyncClient` returns Reactor `Mono` objects for non‑blocking operation and requires an explicit `initialize().block()` call.
@jayessdeesea
基本情報
Instructions for an AI on how to create a Java based mcp server and client
ツール一覧はまだありません
この掲載には表示できるツール一覧がまだありません。サーバーにツールがないという意味ではありません。対応機能はプロジェクトのドキュメントをご確認ください。
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
The Model Context Protocol (MCP) is a standardized protocol for communication between AI models and external tools or resources. This Java SDK provides a robust implementation, enabling Java applications to create MCP servers that expose tools and resources to AI models, as well as MCP clients that communicate with these servers.
Add the MCP BOM to your project's dependency management, then include the core mcp artifact. Use the builder pattern to create a McpSyncClient or McpAsyncClient, providing a transport (e.g., StdioClientTransport) and client info. Then call methods like readResource, callTool, listPrompts, or getPrompt. Close the client after use.
McpSyncClient) and asynchronous (McpAsyncClient) client implementationsMcpSyncServer, McpAsyncServer) for exposing resources and tools`McpSyncClient` blocks on each call, while `McpAsyncClient` returns Reactor `Mono` objects for non‑blocking operation and requires an explicit `initialize().block()` call.
The SDK includes `StdioClientTransport` for stdio‑based communication. HTTP/SSE transports require the `jakarta.servlet-api` dependency (version 5.0.0, scope provided).
Use the MCP BOM (`mcp-bom:0.8.0`) for version management, then add the core `mcp` artifact. For HTTP/SSE, include `jakarta.servlet-api:5.0.0`. Testing utilities are in the `mcp-test` artifact.

SSH MCP server for AI agents: remote commands, file transfer, log search and server audits through OpenSSH.

AI-native payments for tools and APIs. Discover, pay for, execute, and publish monetized APIs directly from your agent, settled per call in USDC over x402, through the Model Context Protocol. payments · finance · x402 ·

Verified distributed compute for humans, applications, and agents. Submit Blender, Octane, and video workloads, route them across qualified GPUs, track asynchronous execution, download finished artifacts, and verify FARP


Catch intent conflicts before code conflicts. The open-source coordination protocol for coding agents, built above Git.
コメント