The Cloud Context Your AI Needs

The Model Context Protocol is an open standard that lets AI tools like Claude Code (CLI), Claude Desktop, Claude Cowork, OpenAI Codex, and ChatGPT Desktop call external capabilities. OpsCanvas arrives as an MCP server, which is why it works inside the AI your engineers already use instead of asking them to adopt another agent.

Tested and supported today: Claude Code (CLI), Claude Desktop, Claude Cowork, OpenAI Codex, and ChatGPT Desktop. Cursor, OpenCode, Antigravity CLI, Gemini Code Assist, and Grok are coming soon. OpsCanvas MCP is a standard MCP server, so it will often work in an MCP-capable tool we have not listed. Coming soon means we have not finished testing it or done the tuning that tool needs, not that it is blocked.

No. The map is built locally, under your own credentials, and it stays on your machine. Your estate is not uploaded, not used for training, and not shared. The model sees answers. It does not get your infrastructure.

Read and understand your estate. Ask for the topology of your most active application, what is costing you the most right now, what nothing is using, what changed overnight, and what sits downstream of anything you are thinking of touching.

Minutes. In the walkthrough above, a six-account estate of 1,180 resources reached a live map in minutes. Larger estates take longer, and you confirm every source before it enters the map.

No. The map is built from runtime behavior and real dependency, not from tags. Tagging projects are incomplete on day one and wrong by day two, which is exactly the gap this closes.

Not in this release. OpsCanvas MCP is read-only today by design, on the principle that trust comes before mutation. It reads, correlates, and explains your estate so you can decide what to change and make the change yourself. Guardrailed remediation with human approval on every write is in development and is not part of what you install today.

Nothing. OpsCanvas MCP is free with an OpsCanvas account, and running it costs $0 extra because it works through the AI subscription you already pay for rather than billing you per token. There is no credit card and no trial clock.

Local. This is Operator, the free edition for the individual engineer: the server runs on your workstation, the map is built and stored there, and there is nothing to provision and no tenant to sign up for. Pro, where a team shares one hosted map, is per seat and is not what the install command above gives you.

No. It reads what your workstation can already reach, using the cloud credentials you have already configured, so there is no new role to provision, no agent to deploy into your accounts, and nothing for anyone to approve before you try it. You confirm each source before it enters your map.

Direct connections give the model raw data, and in our evaluation that was not enough to produce a single correct environment answer: 35 of 35 correct with the graph connected, zero without. Dependencies, blast radius, ownership, and change history live in the graph, not in any single API.

Operator is the name of the free edition: OpsCanvas MCP for one person, on one workstation, local and read only. Pro is the same product for a team, hosted by OpsCanvas. Enterprise is the same product hosted by you. The install command above gives you Operator.

Nothing starts over. When you join a team on Pro, everything you already mapped appears in the team's graph on arrival, and the team gets one combined map, a shared findings queue with ownership, and a record of who asked what and what was approved. Pro is per seat; see pricing.

Oscar is our own command line agent and it continues to ship and work. OpsCanvas MCP is the same graph and the same safety model, delivered inside the tools your engineers already use rather than as another agent alongside them.