list_gradesList the top graded MCP servers from the mcpqueen registry (deterministic probe grades with evidence). Returns grade, score 0-100, latency, tool count and auth state per server.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max servers to return (default 25, max 100) |
| Name | Required | Description | Default |
|---|---|---|---|
| results | Yes | ||
| returned | Yes | ||
| safety_notice | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Output schema / properties / safety_noticeAdded value: +{
+ "type": "string"
+}Output schema / requiredPrevious value: -[
- "returned",
- "results"
-]New value: +[
+ "safety_notice",
+ "returned",
+ "results"
+]Output schema / (root)Previous value: -nullNew value: +{
+ "additionalProperties": false,
+ "properties": {
+ "results": {
+ "items": {
+ "additionalProperties": true,
+ "properties": {
+ "grade": {
+ "type": "string"
+ },
+ "latency_ms": {
+ "type": [
+ "number",
+ "null"
+ ]
+ },
+ "probed_at": {
+ "type": "string"
+ },
+ "protocol_access": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "provisional": {
+ "type": [
+ "number",
+ "boolean"
+ ]
+ },
+ "score": {
+ "type": "number"
+ },
+ "server_name": {
+ "type": "string"
+ },
+ "tool_count": {
+ "type": [
+ "number",
+ "null"
+ ]
+ }
+ },
+ "required": [
+ "server_name",
+ "grade",
+ "score",
+ "provisional",
+ "probed_at"
+ ],
+ "type": "object"
+ },
+ "type": "array"
+ },
+ "returned": {
+ "type": "number"
+ }
+ },
+ "required": [
+ "returned",
+ "results"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true and destructiveHint=false, but the description adds behavioral context by stating grades are 'deterministic probe grades with evidence' and enumerating return fields (score, latency, tool count, auth state). This goes beyond the annotations and clarifies data provenance and ordering.
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 main action and includes relevant return field details without redundancy. It is appropriately sized and structured for quick agent comprehension.
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 list tool with one optional parameter and an output schema, the description covers the source, ordering (top graded), and return fields. It is complete enough to support selection and invocation without ambiguity.
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?
The input schema already fully documents the single limit parameter (default 25, max 100) at 100% coverage. The description does not add any extra meaning to the parameter, so it meets the baseline but doesn't exceed it.
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 tool lists top graded MCP servers from a specific registry, using the verb 'List' and specifying the resource and source. This distinguishes it from siblings like get_server_grade (single server) and search_servers (search semantics). It also includes details about deterministic grades and evidence.
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 description implies use for obtaining a ranked list of top graded servers but does not explicitly mention alternatives or when not to use it. It lacks direct exclusions like 'use search_servers instead when filtering by name.' However, the purpose is clear enough to infer usage context.
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.
Each tool has a clearly distinct purpose: getting grades, detailed evidence, listing top servers, searching servers by task, searching tools, searching trust evidence, and submitting feedback. No two tools overlap in functionality.
All tool names follow a consistent verb_noun pattern using snake_case (e.g., get_server_grade, search_servers, submit_feedback). The naming is predictable and uniform.
With 7 tools, the surface is well-scoped for a registry and evidence server. Each tool serves a distinct purpose, covering retrieval, search, and feedback submission without unnecessary bloat.
The tool set covers core operations (getting grades, search, feedback), but there are minor gaps: no tool to list all servers (only top graded) and no direct way to list tools for a specific server. These are workable but not fully complete.