Search Results for "local server"

MCPB (MCP Bundles) defines a packaging format and toolchain for one-click installation of local Model Context Protocol (MCP) servers in desktop apps like Claude for macOS and Windows. An .mcpb file is a zip archive containing your server and a manifest.json that declares capabilities, entry points, permissions, and configuration inputs, much like how .crx packages Chrome extensions or .vsix packages VS Code extensions. The goal is to make local tool servers easy for end users to install, update, and configure, while giving app developers a consistent way to discover and load them safely. ...

...It is designed to let OpenAI-style clients connect to Gemini-like models through routes such as chat completions, models, responses, and native Gemini-compatible endpoints. The project can run as a simple local server and uses a mostly single-file design with an optional dependency for streaming. It supports model aliases for Flash, Thinking, Pro-style routing, Auto, and Lite variants. The tool also includes optional API keys, function calling, SSE streaming, web search access, Docker deployment, and client examples for OpenAI SDK-style usage. ...

MiMo-V2-Flash is a large Mixture-of-Experts language model designed to deliver strong reasoning, coding, and agentic-task performance while keeping inference fast and cost-efficient. It uses an MoE setup where a very large total parameter count is available, but only a smaller subset is activated per token, which helps balance capability with runtime efficiency. The project positions the model for workflows that require tool use, multi-step planning, and higher throughput, rather than only...

...It can serve as a custom GPT plugin or function-calling backend so that a chat session can “look up” relevant documents based on user queries, inject those results into context, and respond more knowledgeably about a private knowledge base. The repo provides code for ingestion pipelines (embedding documents), APIs for querying, local server components, and privacy / PII detection modules. It also contains plugin manifest files (OpenAPI spec, plugin JSON) so that the retrieval backend can be registered in a plugin ecosystem. Because retrieval is often needed to make LLMs “know what’s in your docs” without leaking everything, this plugin aims to be a secure, flexible building block for retrieval-augmented generation (RAG) systems.

Grok-2.5 is a large-scale AI model developed and released by xAI in 2024, made available through Hugging Face for research and experimentation. The model is distributed as raw weights that require specialized infrastructure to run, rather than being hosted by inference providers. To use it, users must download over 500 GB of files and set them up locally with the SGLang inference engine. Grok-2.5 supports advanced inference with multi-GPU configurations, requiring at least 8 GPUs with more...