get_receipts
Get every target this request fanned out to, each with its delivery receipt or the reason it has none. A still-moving delivery (queued/retrying) answers from the live tracking copy, a terminal one (delivered/failed) from durable storage — the response shape is identical either way, so poll this o...
This record as markdown: /tools/dev-echorelay-management/get-receipts.md
What get_receipts does on EchoRelay
AI agents call get_receipts to retrieve information from EchoRelay without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
requestId | string | Yes | UUID returned by the relay in 202 responses or visible in list_requests rows. |
Parameters from the server's own tool schema.
Why get_receipts is rated Low
Even though get_receipts only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Risk signalsBulk/mass operation — affects multiple targets
Attacks that exploit this kind of access
The rule that runs get_receipts safely
PolicyLayer is an MCP gateway: it sits between your AI agents and EchoRelay, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_receipts, this is the rule to start with:
get_receipts is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect EchoRelay, apply this rule, and every get_receipts call is checked against it from then on.
Questions about get_receipts
Get every target this request fanned out to, each with its delivery receipt or the reason it has none. A still-moving delivery (queued/retrying) answers from the live tracking copy, a terminal one (delivered/failed) from durable storage — the response shape is identical either way, so poll this on an interval with the same requestId a 202 response returned and watch status move to a terminal value. Each entry has targetId, targetURL, available, and when available: status (queued/retrying/delivered/failed), attempt, enqueuedAt/updatedAt/completedAt (unix ms), terminalError, callbackState (none/pending/delivered/failed — whether the target's completion-callback URL, if any, has been notified). When available is false, reason is "sync_or_stream_delivery" (the target answers inside the original HTTP response and is never tracked here — see the response body from that call instead) or "not_found" (no record for this target, e.g. aged past the retention window). It is categorised as a Read tool in the EchoRelay MCP Server, which means it retrieves data without modifying state.
get_receipts accepts 1 parameter: requestId. Required: requestId. The full parameter table on this page comes from the server's own tool schema.
Register the EchoRelay MCP server in PolicyLayer and add a rule for get_receipts: 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 EchoRelay. Nothing to install.
get_receipts is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get_receipts 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 get_receipts. 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.
get_receipts is provided by the EchoRelay MCP server (https://mcp.echorelay.dev). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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