关键词 "Technical specifications" 的搜索结果, 共 17 条, 只显示前 480 条
Compose and generate effortlessly MCP servers from any OpenAPI specifications
JIRA MCP Server: Essential API Integrations for Technical Program Managers
Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.
Powerful bridge between OpenAPI specifications and AI assistants using the Model Context Protocol (MCP). Automatically converts any OpenAPI/Swagger API specification into MCP tools that can be used by
A tool for automatically converting OpenAPI specifications into Model Context Protocol (MCP) Server
A tool that converts OpenAPI specifications to MCP server
Swytchcode accelerates API integrations, allowing developers to seamlessly integrate any API using Postman collections or OpenAPI specifications. With Swytchcode, developers can obtain production-read
A MCP server that enables Claude to discover and call any API endpoint through semantic search. Intelligently chunks OpenAPI specifications to handle large API documentation, with built-in request exe
OpenAPI specifications => MCP (Model Context Protocol) tools
MCP Server (Model Context Protocol) for turning OpenAPI specifications into a MCP Resource
An MCP server providing a range of cryptocurrency technical analysis indicators and strategies.
The OpenAPI to Model Context Protocol (MCP) proxy server bridges the gap between AI agents and external APIs by dynamically translating OpenAPI specifications into standardized MCP tools. This simplif
ReqRefine is an MCP server that enhances requirement gathering through strategic questioning. It guides users to reveal comprehensive needs, uncovers implicit requirements, and transforms dialogue int
Convert OpenAPI specifications to MCP server ready tools
MCP server to interact with the DocumentDB database and perform basic operations. The module has some specifications, based on the business rule we are working on, to manage product catalogs.
Memory Bank is an MCP server that helps teams create, manage, and access structured project documentation. It generates and maintains a set of interconnected Markdown documents that capture different
微软研究院的一个研究团队探索了使用主动式强化学习(agentic reinforcement learning)来实现这一目标,也就是说,模型会与专用工具环境中的工具进行交互,并根据收到的反馈调整其推理方式。而他们的探索成果便是 rStar2-Agent,这是一种强大的主动式强化学习方法。使用该方法,这个微软团队训练了一个 14B 的推理模型 rStar2-Agent-14B—— 该模型达到前沿级
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