Update a datasource's metadata.
AI agents use edit_datasource 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.
This tool modifies datasource metadata reversibly without deleting or executing arbitrary code. It falls under Write rather than Destructive because metadata updates are typically reversible (can be edited again).
From the tool's definition Tool name 'edit_datasource' and description 'Update a datasource's metadata' indicate modification of existing configuration data.
Documented attack patterns abuse exactly the kind of access edit_datasource 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 edit_datasource:
{
"version": "1",
"default": "deny",
"tools": {
"edit_datasource": {
"limits": [
{
"counter": "edit_datasource_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}edit_datasource 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.
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Update a datasource's metadata. 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 edit_datasource: 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.
edit_datasource 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 edit_datasource 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 edit_datasource. 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.
edit_datasource 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.
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20 SLayer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.