Update an existing record in a Dataverse table
AI agents use update_record to create or update resources in Dataverse — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Dataverse environment.
This tool creates or modifies data reversibly by updating records in Dataverse tables. It does not delete data (which would be Destructive), execute arbitrary code (Execute), or move money (Financial).
From the tool's definition Tool name 'update_record' and description 'Update an existing record in a Dataverse table' indicate modification of existing data in a reversible manner.
Documented attack patterns abuse exactly the kind of access update_record gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Dataverse, and nothing reaches the server without passing your rules. This is the rule we recommend for update_record:
{
"version": "1",
"default": "deny",
"tools": {
"update_record": {
"limits": [
{
"counter": "update_record_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}update_record 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 an existing record in a Dataverse table. It is categorised as a Write tool in the Dataverse MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Dataverse MCP server in PolicyLayer and add a rule for update_record: 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 Dataverse. Nothing to install.
update_record 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 update_record 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 update_record. 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.
update_record is provided by the Dataverse MCP server (rededis/dataverse-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Dataverse, 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.
22 Dataverse tools catalogued and risk-classified — across an index of 43,000+ MCP servers.