kynth-mcp
Server Quality Checklist
Latest release: v0.1.2
- Disambiguation5/5
The two tools are completely distinct: one checks government website accessibility, the other checks nonprofit tax status. There is no overlap or ambiguity between them.
Naming Consistency5/5Both tools follow the exact same 'lookup_*' pattern with a clear noun, making the naming consistent and predictable.
Tool Count4/5With only two tools, the server is slightly under the typical range, but each tool addresses a specific, well-defined lookup need, so the count is reasonable for a niche server.
Completeness4/5Each tool fully covers its intended lookup scenario (accessibility report and nonprofit status). No obvious missing operations exist for the stated purpose, though the overall scope is limited.
Average 4.4/5 across 2 of 2 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 17 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
This server has been verified by its author.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses key behavioral details: the data sources checked, the types of returned information, and the meaning of 'clear'. It does not mention any limitations, caching, or error conditions, but for a lookup tool this is quite transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: two sentences, the first stating the main action and data sources, the second defining the key result. Every sentence adds value, with no fluff or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with one parameter, no output schema, and no annotations, the description is complete: it identifies the exact lists, the return values, and the meaning of a clear result. It gives the user sufficient understanding without needing to guess return structure or side effects.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers 100% of the parameter 'ein' with a description and example. The tool description mentions 'by EIN' but adds no new meaning beyond the schema. Thus the baseline score of 3 applies; the description does not need to compensate for schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks a US nonprofit's standing by EIN against specific IRS and California lists, enumerating exactly what is checked (auto-revocation, delinquency/suspension) and what is returned (dates, reinstatement window, AB 488 effect). This distinguishes it from the sibling lookup_ada_report and uses a specific verb ('Check') with a well-defined resource.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context about the tool's scope (IRS and California lists) and what constitutes a 'clear' result, but it does not explicitly state when to use this tool versus alternatives or any exclusions. Since the sibling tool is not referenced, it lacks explicit when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It discloses what the tool returns in detail and implies a read-only operation via the verb 'look up'. It doesn't mention error handling for domains not in the index, but this is minor for a lookup tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is tightly written: it leads with the action, summarizes the return payload, gives example questions, and includes the protocol-stripping note. Every sentence earns its place without redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter lookup with no output schema, the description fully covers what the tool does, what it returns, and when to use it. It is self-contained and sufficient for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already fully documents the single parameter. The description adds valuable behavior beyond the schema, noting that protocol and paths are stripped automatically, which helps the agent construct valid input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the specific verb 'look up' and the resource 'CivicBinder Municipal Web Accessibility Index', and lists the specific return fields (grade, violation counts, failing rules, deadline, link). It clearly differentiates from the sibling tool lookup_nonprofit_status, which is about a different subject entirely.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context with example questions ('is cityofx.gov ADA compliant') and explicit scope (.gov domains). It doesn't explicitly state when not to use it, but the sibling tool is obviously different in domain, so the guidance is adequate.
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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