Skip to main content
Glama
atomno-mcp

mcp-trademarks

Server Quality Checklist

92%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.4

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: similarity assessment (assess_similarity), status lookup by ID (get_trademark_status), international registry search (search_tmview), and national registry search (search_trademark). No overlap or ambiguity.

    Naming Consistency5/5

    All names follow a consistent verb_noun pattern using lowercase underscores: assess_similarity, get_trademark_status, search_tmview, search_trademark. The pattern is predictable and uniform.

    Tool Count5/5

    With 4 tools, the server is well-scoped for its purpose—covering search (national and international), status retrieval, and similarity assessment. No excess or deficiency for the domain.

    Completeness4/5

    Core trademark workflows are covered: national search, international search, status lookup, and similarity assessment. Missing features like batch search or portfolio management, but these are reasonable exclusions for the stated scope.

  • Average 3.3/5 across 4 of 4 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 7 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • 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.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

  • Behavior2/5

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

    With no annotations provided, the description carries full responsibility for behavioral disclosure. It mentions a 'Pro tariff', implying potential cost or access restrictions, but does not detail authentication needs, rate limits, or side effects. The core search behavior is clear, but transparency is minimal.

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

    Conciseness4/5

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

    The description is a single sentence that efficiently conveys the core purpose. However, it includes the phrase 'Тариф Pro' (Pro tariff), which may be superfluous and not immediately relevant for tool invocation, slightly reducing conciseness.

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

    Completeness3/5

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

    Given the 4 parameters, the presence of an output schema, and no annotations, the description adequately covers the main function but lacks completeness. Missing details include when to prefer this over sibling tools, output format summary, and any prerequisites or limitations, leaving gaps for an AI agent.

    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?

    The input schema has 100% description coverage, with each parameter (query, limit, classes, status_filter) documented clearly. The description adds context about the registry (FIPS/Rospatent) but does not enhance parameter meaning beyond what the schema provides. Baseline 3 is appropriate.

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

    Purpose4/5

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

    The description clearly states that the tool searches for identical or similar trademarks/applications by word designation from the FIPS/Rospatent registry, using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like search_tmview, which may have similar functionality, so it scores 4 rather than 5.

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

    Usage Guidelines2/5

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

    The description provides no guidance on when to use this tool versus alternatives such as assess_similarity, get_trademark_status, or search_tmview. No exclusions or context for preferred usage are given, leaving the agent to infer from the tool name and registry mention.

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

  • Behavior2/5

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

    No annotations are provided, so the description must carry full burden. It mentions 'reference assessment' and 'not a guarantee', and briefly covers risk levels, but lacks disclosure on behavioral traits like rate limits, authorization, or error behavior.

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

    Conciseness4/5

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

    The description is a single sentence that conveys key information (purpose, risk levels, caveat, pricing tier). However, the use of Russian may limit accessibility for non-Russian agents; structure is otherwise efficient.

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

    Completeness3/5

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

    Given the tool has an output schema (unknown contents), the description minimally covers what it does and what it returns (risk levels). However, it lacks detail on the meaning of risk levels or the comparison dimensions (phonetic/graphic/semantic) and how they relate to output.

    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 coverage is 100% (all parameters have descriptions). The description adds minor context beyond schema (e.g., phonetic/graphic/semantic), but does not significantly enhance parameter understanding beyond the existing schema descriptions.

    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 clearly states the tool assesses similarity for confusion (phonetic/graphic/semantic) and outputs risk levels. It distinguishes from siblings (get_trademark_status, search_tmview, search_trademark) which handle status and general searching, not similarity.

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

    Usage Guidelines3/5

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

    The description implies the tool is for similarity assessment but provides no explicit guidance on when to use it versus alternatives, nor any conditions or exclusions.

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

  • Behavior2/5

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

    No annotations are provided, so the description carries full burden. It notes the tool is for 'open TMview database' and 'Pro tariff' but does not disclose read-only nature, rate limits, authentication needs, or any side effects. The behavioral transparency is insufficient.

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

    Conciseness4/5

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

    The description is very short and front-loaded, conveying the tool's purpose quickly. However, it lacks proper sentence structure and additional context that might be expected for a Pro tariff tool.

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

    Completeness3/5

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

    With only 3 parameters and an output schema present, the description covers the basics but omits important context such as what the 'Pro tariff' implies, whether the tool is available to all users, and limitations of the search.

    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 baseline is 3. The description mentions 'словесное обозначение' for query, matching the schema, but adds no extra detail like format or examples. It does not improve understanding beyond the schema.

    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 clearly states the tool performs international trademark searches in the TMview database (foreign registers), distinguishing it from sibling tools like search_trademark which likely covers domestic data.

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

    Usage Guidelines3/5

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

    The description provides minimal guidance on when to use this tool vs alternatives. It mentions 'Pro tariff' hinting at paid usage but does not explicitly state when not to use or compare to siblings.

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

  • Behavior2/5

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

    No annotations are provided, so the description must fully disclose behavioral traits. It only lists output fields but does not mention idempotence, error handling, authentication needs, or rate limits. The 'Тариф Pro' hint is insufficient.

    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 extremely concise, with a single sentence covering purpose and output fields, plus a tariff note. No redundant words, and the important information is front-loaded.

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

    Completeness4/5

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

    Given the output schema exists (context indicates it does), the description omits return-value details, which is acceptable. It lists key output fields. However, it lacks error-handling or validation hints, which would make it more complete.

    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 coverage is 100%, and the parameter description in the schema is adequate. The tool description does not add further semantic detail beyond restating the parameter purpose, so it meets the baseline without adding extra value.

    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 clearly states the tool retrieves trademark status by application/certificate number, listing specific fields (priority, registration, Nice classes, rights holder, term). It distinguishes itself from sibling tools which are for similarity assessment and search.

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

    Usage Guidelines3/5

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

    The description implies usage when a number is available and status is needed, but offers no explicit guidance on when to use versus alternatives like search_trademark or assess_similarity, nor any exclusions.

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

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

mcp-trademarks MCP server

Copy to your README.md:

Score Badge

mcp-trademarks MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/atomno-mcp/mcp-trademarks'

If you have feedback or need assistance with the MCP directory API, please join our Discord server