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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.
Coder
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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, Coder seems to be more popular. It has been mentiond 62 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.
Oh this is awesome, will take a look. Iโve had rough experiences with Kubeflow in the past, recently Iโve been using Coder workspaces https://coder.com/ and itโs pretty good but less ML/AI integrated (but, stitched together with Ray autoscaling nodes it can get really nice). - Source: Hacker News / 16 days ago
I'm using https://coder.com for all my development containers. I've got mine hooked up to a k8s cluster, but anything that you can provision with Terraform can be used (e.g. Docker containers). - Source: Hacker News / about 2 months ago
Coder | https://coder.com/ | Multiple roles | Multiple locations | Full-time Coder is an AI software development company leading the future of autonomous coding. We empower teams to build software faster, more securely, and at scale through the collaboration of AI coding agents and human developers. Our mission is to make agentic AI a safe, trusted, and integral part of every software development lifecycle.... - Source: Hacker News / about 2 months ago
Ollama is fantastic for ollama pull model && ollama run model. It's genuinely the best way to get started with local models. But when you're running them as infrastructure โ serving through an OpenAI-compatible API to Coder Agents, IDE extensions, and automation โ the abstraction layer starts to chafe. - Source: dev.to / 3 months ago
Run agents, lots of them, using this open source project - link [tool] - ( Added: 2026-04-11 07:42:11 ). - Source: dev.to / 3 months ago
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