ingest_datasource_models
AI agents use ingest_datasource_models to create or update resources in SLayer — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your SLayer environment.
The name suggests ingesting (importing/loading) models into a datasource, which implies creating or modifying data. Based on sibling tools like 'create_model', 'edit_model', and 'create_datasource', this tool likely writes/imports model definitions. However, the empty description significantly lowers confidence. It could also be Execute if it triggers a pipeline.
From the tool's definition Tool name 'ingest_datasource_models' — no description provided
Documented attack patterns abuse exactly the kind of access ingest_datasource_models gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and SLayer, and nothing reaches the server without passing your rules. This is the rule we recommend for ingest_datasource_models:
{
"version": "1",
"default": "deny",
"tools": {
"ingest_datasource_models": {
"limits": [
{
"counter": "ingest_datasource_models_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}ingest_datasource_models stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
Free to start. No card required.
ingest_datasource_models. It is categorised as a Write tool in the SLayer MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the SLayer MCP server in PolicyLayer and add a rule for ingest_datasource_models: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches SLayer. Nothing to install.
ingest_datasource_models is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the ingest_datasource_models rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for ingest_datasource_models. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
ingest_datasource_models is provided by the SLayer MCP server (motleyai/slayer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from SLayer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
20 SLayer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.