FREE, no payment required. Full transparency into what you pay for: returns the exact criteria MCP Judge uses to score an MCP server — each criterion, its weight out of 100, and the A-F grade scale. Call this to understand how quick_check, evaluate_mcp and compare_mcps score targets before paying. The evaluation is fully objective and automated — no human reviewer and no AI opinion. Takes no parameters.
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Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full load. It discloses that the tool is FREE and that the evaluation is 'fully objective and automated — no human reviewer and no AI opinion', which are useful behavioral traits beyond what a schema would show. It also notes it takes no parameters, though that is already implicit in the empty schema.
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 not overly long (~70 words) and front-loads the most important fact ('FREE, no payment required'). However, there is minor redundancy ('FREE' and 'no payment required') and some promotional phrasing ('Full transparency into what you pay for'), though it remains efficient overall.
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 zero-parameter tool with no output schema, the description is complete. It explains what the tool returns (criteria, weights, grade scale), why to call it (before paying for scoring tools), and the nature of the evaluation (objective/automated). An agent has everything needed to invoke it correctly without further inference.
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 tool has zero parameters, and the schema description coverage is 100% (empty). According to the calibration guidance, 0 params warrants a baseline of 4. The description adds a note that it 'Takes no parameters' but otherwise does not need to explain parameter semantics.
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 states a specific verb ('returns') and a clear resource ('the exact criteria MCP Judge uses to score an MCP server'), including what is returned (criteria, weights, grade scale). It distinguishes itself from siblings by positioning it as the transparency tool that explains the scoring of quick_check, evaluate_mcp, and compare_mcps.
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 explicitly says 'Call this to understand how quick_check, evaluate_mcp and compare_mcps score targets before paying', giving clear contextual guidance on when to use it (before paid tools). While it does not state exclusions or alternatives, the 'before paying' instruction is a strong usage signal.
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 distinct role: quick_check for fast screening, evaluate_mcp for detailed single-server evaluation, compare_mcps for head-to-head comparison, and list_criteria for transparency. No two tools overlap in purpose, so there is no ambiguity in selection.
All tools follow a consistent verb_noun snake_case pattern (quick_check, evaluate_mcp, compare_mcps, list_criteria), making the set predictable and easy to navigate. The naming convention is uniform across all four tools.
The server has exactly 4 tools, which is well-scoped for its purpose. Each tool covers a distinct aspect of evaluating MCP servers, and there is no redundancy or bloat. The count feels intentional and complete.
The toolset covers the full user journey for evaluating MCP servers: free quick screening (quick_check), in-depth analysis (evaluate_mcp), comparison between options (compare_mcps), and access to scoring criteria (list_criteria). There are no obvious gaps in lifecycle coverage.