get_project
Get the EchoRelay project this token is scoped to: id, slug, name, caller-facing API base URL, whether the token has edit access, and the request-log hot-tier retention window.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Get the EchoRelay project this token is scoped to: id, slug, name, caller-facing API base URL, whether the token has edit access, and the request-log hot-tier retention window.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds value by specifying the response fields (id, slug, name, API base URL, edit access, retention window), which provides useful context about what the tool exposes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the purpose ('Get the EchoRelay project this token is scoped to') and then enumerates the key fields. There is no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple, read-only, zero-parameter tool with no output schema, the description fully specifies what the tool returns. It is complete and leaves no ambiguity about the tool's behavior or output.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so the schema imposes no burden. The description confirms no inputs are required and instead lists outputs, which is appropriate for a zero-input tool. Baseline 4 is warranted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'EchoRelay project' with a specific scope ('this token is scoped to'). It also lists the exact fields returned, distinguishing it from sibling get_* tools like get_endpoint or get_billing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: use this tool when you need the project associated with the current token. It does not explicitly mention alternatives or exclusions, but the unique token-scoping phrase makes the intended usage unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.