EchoRelay

list_dlq

Read-only

List entries currently in this project's dead-letter queue, newest first. One inbound request fans out per-target, so a single failed request may produce several DLQ entries with different targetIds. Returns {total, limit, offset, rows[], evictedCount} where each row has id (Redis stream id), requestId, targetId, configVersion (the published config that authorised the delivery; 0 means unstamped), failureReason, failedAttempts, failedAt, payload (the original Consumer queue entry JSON); evictedCount is the lifetime count of entries the queue's capacity cap discarded before they could be triaged. DLQ entries — including the original request body and headers — are kept for up to 30 days from the failure time or until cleared, then purged automatically (or discarded early past capacity — see evictedCount); they are never written to a database. get_request still answers what happened to a purged/evicted/discarded entry's inbound request for the project's requestLogRetentionDays window, independent of whether the DLQ row itself still exists. requestId is the durable handle across a retry: an entry's own id changes every time it is replayed and later dead-letters again, so get_dlq_entry accepts a requestId lookup as well as id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Page size. Default 50.
`offset`	No	Page offset. Default 0.

TDQS

A4.5/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description goes far beyond that by disclosing return shape, eviction behavior, 30-day retention, non-persistence to DB, and the durable requestId relationship across replays. This adds critical behavioral context not available in annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, then efficiently packs essential details about fan-out, return structure, retention, and related tools. Every sentence adds valuable information, and the structure flows logically from listing to behavioral nuances.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description fully documents the return object and each field. It also covers edge cases like eviction, purging, and the relationship to get_request, making it complete for an agent to understand the tool's behavior without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description doesn't add parameter-specific details beyond the schema, but the schema already documents limit and offset adequately. The description's mention of 'newest first' and 'evictedCount' indirectly relates to pagination and capacity but doesn't add parameter syntax.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'List entries currently in this project's dead-letter queue, newest first.' It clearly distinguishes from sibling tools like get_dlq_entry (single entry retrieval) and discard_dlq_entry/retry_dlq_entry (mutations).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context on when to use this listing tool by explaining fan-out behavior and how it relates to get_request for purged entries. It also mentions get_dlq_entry accepts requestId lookup, implying the distinction between listing and single-entry retrieval, though it doesn't explicitly state 'use this instead of X'.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.6/5.0

Disambiguation3/5

Most tools target distinct resources and the descriptions are unusually explicit, but the billing cluster (change_plan/cancel_subscription and the many add-on actions) plus the preview/diff tools overlap and could cause mis-selection. config_diff, dry_run_endpoint, and preview_line_draft all read as 'preview what will change' at first glance despite different scopes.

Naming Consistency4/5

The overwhelming majority follow a clean snake_case verb_noun pattern: create_*, get_*, list_*, set_*, update_*, delete_*. It is only held back by a few naming outliers such as config_diff and default_endpoint_template, which break the verb-first convention.

Tool Count1/5

78 tools is an extreme mismatch for an MCP server surface, even accounting for the broad management/relay domain. Such a large surface will overwhelm model context and make tool selection materially harder; this would be better split into focused servers for configuration, data-plane operations, and billing.

Completeness4/5

The tool surface is very thorough: projects, lines, endpoints, credentials, keys, configs/drafts, DLQ, requests, metrics, audit, team, and billing are all represented. Only minor gaps exist, such as no direct single-line get/update and the intentional inability to widen the outbound allowlist or lift archive protection via API.

Resources

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