Client to ONVIF NVT devices Profile S: cameras
Most knowledge and memory work still happens through a UI a human drives. Onvif MCP server moves it into the conversation instead. Client to ONVIF NVT devices Profile S: cameras.
ONVIF Client protocol Profile S (Live Streaming) and Profile G (Replay) Node.js implementation.
The server publishes 2 tools. What each one is for:
Tests — By default the tests use a mockup server to generate ONVIF repliesDocumentation — To build jsdoc for the library with default theme run npm run jsdoc. Otherwise use jsdoc with sources from ./lib/*.jsThe server ships on npm as onvif, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
This sits in the knowledge and memory group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Onvif's toolset — Tests, Documentation — is a fair guide to whether it matches your workflow. It is maintained by agsh; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Tests | By default the tests use a mockup server to generate ONVIF replies. |
| Documentation | To build jsdoc for the library with default theme run npm run jsdoc. Otherwise use jsdoc with sources from ./lib/*.js |
{
"mcpServers": {
"onvif": {
"command": "npx",
"args": ["-y", "onvif"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.