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    Model Context Protocol server for AI Canvas. Search, inspect, and install open-source React and Tailwind components from the aicanvas.me registry directly in your AI editor.
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    MIT
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    Simulate hundreds of AI agents to predict how communities react to events and policies. Upload any document (PDF, Markdown, text) and DeepMiro spawns a diverse swarm of AI agents that debate, share, and form opinions — then delivers a calibrated prediction report. Free and open-source.
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    AGPL 3.0
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    An MCP server that turns the ModelRadar catalog into a model router between OpenRouter and your CLI or agent, enabling discovery, recommendation, and execution of language models.
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    MIT
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    Enables agents to connect through a single gateway that has a decision model pick which MCP tools and playbooks are relevant to each request, so the LLM only sees the few schemas it needs, and to then invoke those tools on the underlying servers. This cuts tool-selection cost and prompt size dramatically when many MCP servers are connected.
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    MIT
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    Enables AI coding agents to make fast, zero-output-token decisions by evaluating context, diffs, logs, or options through the OpenRouter Decisions API using TypeSafe Jev, returning calibrated probabilities for binary, categorical, or scoring questions.
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    32 npm
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    MIT
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    Enables Claude Code and Codex Herdr workers to get local, advisory routing decisions by selecting a client, model, effort tier, and worker launch instruction for a stage, and by ranking a short list of bounded next actions. Decisions come from a selectable local backend (Laya or a local Kev model), returning confidence and uncertainty without executing anything or granting permissions.
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    MIT
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    Provides agents with MCP tools for typed probabilistic decisions—Choice, Noul, and Score—with calibrated probabilities and abstention, using local OpenAI-compatible models via LM Studio logprobs.
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    Routes your AI tasks to the best available model across 20+ providers — automatically selecting based on task type, budget, and subscription pressure. Supports text, image, video, and audio with built-in cost optimization and fallback chains.
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    Enables agents and users to route prompts to the cheapest reachable free or paid model across providers, compare costs, list filtered models, and receive fallback chains and cached routing results without calling any LLM API.
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    Enables PPT generation using iFlytek Zhiwen API, supporting multiple transport protocols (HTTP, SSE, HTTP-Stream) and ReACT workflows for intelligent template selection, content generation, and document-to-PPT conversion.
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    MIT