Gradio
Hugging Face
Streamlit
Anvil.works
PyTorch
Flet
Civitai
DuckDuckGo
Emisar.dev
Emisar is the last MCP server youโll need to install: a Zero-Trust gateway connecting Claude, Cursor, ChatGPT, and any AI agent to your infrastructure. One server handles production access, debugging, alerts, and internal operations, with new capabilities added as packs. Agents can inspect real production state, debug what they shipped, and help resolve incidents. Safe reads run automatically; policy allows, blocks, or routes risky actions for approval. No SSH keys, VPNs, remote shells, or standing shell access โ and every call is recorded.
Gradio Emisar.devNo features have been listed yet.
No Emisar.dev videos yet. You could help us improve this page by suggesting one.
Emisar.dev's answer:
emisar is for SRE, DevOps, platform engineering, infrastructure, and security teams that want AI agents to inspect and operate production systems. It is especially relevant to teams managing multiple Linux hosts, clusters, databases, cloud services, or regulated environments where unrestricted shell access and incomplete audit records are unacceptable.
Emisar.dev's answer:
The hosted control plane and operator interface use Elixir, Phoenix, LiveView, PostgreSQL, and Tailwind CSS. The host runner and MCP bridge are written in Go. Action packs use YAML and JSON Schema, while production infrastructure is managed with Terraform on Google Cloud. The system communicates through MCP, OAuth 2.1, TLS, and WebSockets.
Emisar.dev's answer:
Emisar.dev's answer:
Founder Andrii Dryga spent a decade working as a CTO, full-stack engineer, SRE, and DevOps engineer. He experienced the cost of running the wrong command on the wrong cluster, while also seeing AI solve operational problems in seconds. emisar grew from the need to preserve both truths: AI agents are useful, and production access must remain bounded. Its answer is to give agents a reviewed catalog of operations instead of a blank terminal.
Emisar.dev's answer:
emisar lets AI agents work on real infrastructure without giving them a shell. Agents choose from a finite catalog of typed, versioned actions. Policy decides what runs, what requires approval, and what is denied, while an outbound-only runner verifies the action again on the host. New capabilities arrive as packs behind the same MCP integration, and every request is recorded in both a searchable audit trail and a tamper-evident host journal. [
Emisar.dev's answer:
Choose emisar when you want an agent to keep investigating and handling routine operations without handing it SSH credentials or supervising every call. Compared with raw shell access, copy-paste workflows, or one-off MCP servers, emisar provides reviewed action contracts, host-level enforcement, risk-based policy, scoped access, approvals, pack integrity checks, and a durable audit trail. It is built specifically for governed infrastructure access rather than generic automation.
Based on our record, Gradio seems to be more popular. It has been mentiond 32 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Since we wanted Shayla to feel approachable, we went with a simple chatbot interface. Pairing a generative AI agent like Gemini with Gradio turned out to be a great fit not just for its flexibility, but because the default chatbot design had a warm, inviting feel. The soft color palette and clean layout made it easier to create a space that felt safe, not clinical. From there, we thought things were going to be a... - Source: dev.to / over 1 year ago
This project contains the code for training and deploying a UNET model for water body segmentation from satellite images. The model is trained on the Satellite Images of Water Bodies from Kaggle. The model is trained using PyTorch and deployed using Gradio on Hugging Face Spaces. - Source: dev.to / over 1 year ago
In this tutorial, we will build a very simple python application with Gradio, a popular framework to build elegant and beautiful frontend for AI/ML python apps. - Source: dev.to / almost 2 years ago
The issue is running the model. Exl2 is part of the ExllamaV2 library, but to run a model, a user needs an API server. The only option out there was using text-generation-webui (TGW), a program that bundled every loader out there into a Gradio webui. Gradio is a common โbuilding-blockโ UI framework for python development and is often used for AI applications. This setup was good for a while, until it wasnโt. - Source: dev.to / about 2 years ago
Exciting! I'm surprised to see nobody has mentioned gradio yet. It seems to sit in the same niche as streamlit and mesop. https://gradio.app/. - Source: Hacker News / about 2 years ago
Hugging Face - The AI community building the future. The platform where the machine learning community collaborates on models, datasets, and applications.
Streamlit - Turn python scripts into beautiful ML tools
Anvil.works - Build seriously powerful web apps with all the flexibility of Python. No web development experience required.
PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...
Flet - Build internal web apps quickly in the language you already know.
Civitai - Civitai is the only Model-sharing hub for the AI art generation community.