Propose a write to the substrate. Use to record an entity, decision, commitment, or learning. Phase 0: every action is auto-approved and executed immediately; the audit ledger captures it either way. A future phase will gate certain capabilities behind human approval. Capabilities available in Ph...
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AI agents use propose_action to create or modify resources in Mcp. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call propose_action repeatedly, creating or modifying resources faster than any human could review. PolicyLayer's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Mcp.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
{
"version": "1",
"default": "deny",
"tools": {
"propose_action": {
"limits": [
{
"counter": "propose_action_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}See the full Mcp policy for all 47 tools.
These attack patterns abuse exactly the kind of access propose_action gives an agent. Each links to the full case and the policy that stops it:
Other write tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.
Propose a write to the substrate. Use to record an entity, decision, commitment, or learning. Phase 0: every action is auto-approved and executed immediately; the audit ledger captures it either way. A future phase will gate certain capabilities behind human approval. Capabilities available in Phase 0: - upsert_entity — create or update a person, company, project, etc. - update_entity — modify fields on an existing entity by id - record_decision — note a decision in institutional memory - record_commitment — record something owed to/from an entity - record_learning — capture what you learned from an outcome Returns: { action_id, verdict, requires_approval, result? }. It is categorised as a Write tool in the Mcp MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the MCP server in PolicyLayer and add a rule for propose_action: 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 Mcp. Nothing to install.
propose_action 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 propose_action 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 propose_action. 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.
propose_action is provided by the MCP server (@butterbase/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 47 Mcp tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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