Integration
Connect Azurevirtualmachines to TensorFeed
When New Virtual Machine fires in Azurevirtualmachines, your agent runs Buy credits in TensorFeed. Describe the whole flow and it is built, tested on every scenario and kept running.
What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it.
Build solutions, not workarounds.
What do you want Azurevirtualmachines and TensorFeed to do together?
Ask the assistant
Connect your AI client
Give your AI client this address.
https://mcp.apiant.aiOne connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser.
Set it up in your client
Claude Code
Run this in the directory you want to work in.
claude mcp add --transport http -s project apiant-ai https://mcp.apiant.aiStart Claude Code there, approve the server, and sign in in the browser page it opens.
Claude Code guide (opens in a new tab)Claude, web and desktop
Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first.
Setup guide (opens in a new tab)Cursor
Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser.
Setup guide (opens in a new tab)Zed
Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server.
Setup guide (opens in a new tab)Codex and the ChatGPT desktop app
Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in.
Setup guide (opens in a new tab)Any other MCP client
Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection.
Setup guide (opens in a new tab)Example flows
What Azurevirtualmachines can start in TensorFeed
When New Virtual Machine in Azurevirtualmachines
then Buy credits in TensorFeed
Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships.
Everything your agent can do with Azurevirtualmachines and TensorFeed
Triggers and actions 1 trigger · 38 actions
- New Virtual Machine
Triggers when a new virtual machine appears in an Azure subscription.
- Deallocate Virtual Machine
Shuts down an Azure virtual machine and releases its compute resources, so compute charges stop until it is started again.
- Get Virtual Machine
Returns a virtual machine's details and its current power state (running, stopped or deallocated).
- List Available VM Sizes
Returns the virtual machine sizes offered in an Azure region, with CPU and memory, and whether each is available to the subscription.
- List Locations
Returns the Azure regions available to a subscription.
- List Resource Groups
Returns the resource groups in an Azure subscription.
- List Subscriptions
Returns the Azure subscriptions the connected app registration can access.
- List Virtual Machines
Returns every virtual machine in an Azure subscription, with its size, region and resource group.
- List Virtual Machines in Resource Group
Returns the virtual machines in one Azure resource group, with their size and region.
- Power Off Virtual Machine
Powers off an Azure virtual machine. The machine stops running but stays allocated, so compute charges continue; use Deallocate Virtual Machine to stop them.
- Restart Virtual Machine
Restarts a running Azure virtual machine. Azure accepts the request and reboots the machine in the background.
- Start Virtual Machine
Starts a stopped or deallocated Azure virtual machine. Azure accepts the request and powers the machine on in the background.
- Buy credits
Initiate a credit purchase against a sender wallet.
- Find AI news
Full-text search across the AI news archive.
- Get AFTA adopter directory
Fetch the machine-readable AFTA adopter directory.
- Get AI agent directory
Fetch a curated directory of AI agents and frameworks.
- Get AI benchmark scores
Fetch public benchmark scores for major AI models.
- Get AI ecosystem daily brief
Fetch a composite daily brief covering the AI ecosystem.
- Get AI model pricing and specs
Fetch pricing and specs for AI models.
- Get AI news
Fetch aggregated AI news articles.
- Get AI podcast episodes
Fetch recent AI podcast episodes.
- Get AI service status
Fetch operational status for major AI services.
- Get benchmark trust verdict
Fetch a trust band and score for an AI benchmark.
- Get cheapest GPU offer
Fetch the cheapest current offer for a canonical GPU.
- Get cross-provider model catalog
Fetch a cross-provider AI model catalog snapshot from OpenRouter.
- Get failover verdict
Fetch the best operational failover target when a provider degrades.
- Get GPU rental pricing
Fetch current GPU rental pricing snapshot.
- Get HF daily papers
Fetch Hugging Face Daily Papers with community signal.
- Get historical snapshot
Fetch one historical daily snapshot by date and type.
- Get hot AI GitHub issues
Fetch currently-hot GitHub issues across AI repos.
- Get LLM endpoint latency probes
Fetch the last 24 hours of LLM endpoint latency probes.
- Get MCP server registry snapshot
Fetch a daily summary of the MCP server registry.
- Get model deprecation calendar
Fetch the AI model deprecation calendar.
- Get recent arXiv papers
Fetch the most recent AI/ML arXiv submissions.
- Get stack safety verdict
Fetch a GO/HOLD/BLOCK deploy gate verdict for an AI-stack package.
- Get trending AI GitHub repos
Fetch trending GitHub repositories in AI.
- Get trending AI papers
Fetch daily citation-ranked AI/ML papers from Semantic Scholar.
- Get trending Hugging Face models
Fetch top trending Hugging Face models, datasets, and Spaces.
- Get trending Reddit AI threads
Fetch currently-hot AI discussion threads on Reddit.
No trigger or action matches that. Ask your agent to add it: it reads the API documentation and builds what you describe.
Each app on its own
Reviews
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More into TensorFeed
Questions
Azurevirtualmachines and TensorFeed, answered
What can start an automation from Azurevirtualmachines?
Any of Azurevirtualmachines's 1 trigger in the catalog, including New Virtual Machine. Describe the moment in plain language and your agent picks the right one.
What can your agent do in TensorFeed when something happens in Azurevirtualmachines?
Any of TensorFeed's 27 actions, including Buy credits, Find AI news, Get AFTA adopter directory and Get AI agent directory. Your agent maps the data both ways and tests every scenario before it ships.
Can it also run from TensorFeed to Azurevirtualmachines?
TensorFeed has no triggers in the catalog today, so automations start in Azurevirtualmachines. If you need the other direction, ask: your agent reads TensorFeed's API documentation and adds it.
Do I have to build a connector for Azurevirtualmachines or TensorFeed?
No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running.
Can my AI client use Azurevirtualmachines and TensorFeed without building an automation?
Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both.
What happens when something fails?
Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships.
Is there a free plan?
Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.