Skip to main content
Glama
StanimirTenev

qrp-mcp

by StanimirTenev
OverviewSchemaRelated ServersScoreDiscussions
Python
Local

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.2.0

  • Disambiguation5/5

    The two tools have entirely distinct purposes: scan_repo performs the actual scanning, while list_algorithms provides reference information. There is no overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern in snake_case (scan_repo, list_algorithms). The naming convention is uniform and predictable.

    Tool Count4/5

    With only two tools, the set is minimal, but it is appropriate for the narrow purpose of scanning for quantum-vulnerable cryptography. The tools cover the core action and supporting reference data without unnecessary extras, making it reasonable despite being below the typical range.

    Completeness5/5

    The tool surface covers the full workflow: scanning a repository and understanding the algorithm classifications. There are no significant missing operations for this focused domain, as scan_repo already returns detailed findings and summaries.

  • 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
    • 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 status not available

  • This repository is licensed under Apache 2.0.

  • 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.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

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

  • Behavior3/5

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

    No annotations are provided, so the description carries the full burden. It does disclose the classification categories and the server-scoped nature, but it does not explicitly state the operation is read-only, non-mutating, or safe to call, which is a minor gap for a tool without annotations.

    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 a single concise sentence that front-loads the action ('List') and includes all necessary details without fluff. Every word earns its place.

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

    Completeness5/5

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

    For a parameterless list tool, the description is complete: it says what is listed and how it is classified. The presence of an output schema means the return format is already documented, so no additional return-value explanation is needed.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The tool has zero parameters, so the empty schema already covers everything. The description doesn't need to explain parameters, and the 100% schema coverage confirms no parameter semantics are missing.

    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 uses a specific verb ('List') and identifies a clear resource ('algorithm families this server recognises') plus the classification detail. It clearly distinguishes from the sibling tool 'scan_repo' by focusing on a read-only inventory rather than scanning.

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

    Usage Guidelines4/5

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

    The description implies the tool is for when you need to know recognized algorithm families and their classifications. It doesn't explicitly name alternatives or exclusion criteria, but given the sibling tool is unrelated, the context is reasonably clear.

    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?

    With no annotations, the description carries the disclosure burden. It states 'Runs entirely on this machine -- no network calls, nothing uploaded,' providing a privacy guarantee, and clarifies the scope of files read. It also briefly describes the output, adding meaningful behavioral context beyond the schema.

    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 front-loads the core purpose in the first sentence, then adds scope, output, privacy note, and an Args section for the parameter. It is concise and every sentence contributes value.

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

    Completeness5/5

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

    The tool takes one simple parameter, and an output schema is present, so the description does not need to detail return values. It covers what the tool does, what it reads, privacy, and input format. Together with the output schema, this is fully sufficient.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema for `path` has only a title with no description (0% coverage). The description compensates with 'Directory to scan (e.g. a checked-out repository),' adding both meaning and an example. For a single parameter, this is sufficient.

    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 explicitly states 'Scan a local directory for cryptography that a quantum computer would break.' This pairs a specific verb ('scan') with a concrete resource ('local directory') and a clear goal, and it differentiates from sibling list_algorithms by describing the full scan output (algorithms, findings, exposure summary).

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

    Usage Guidelines4/5

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

    It gives clear context: scanning a local directory and reading source/config files. However, it does not explicitly name the sibling alternative list_algorithms or state when not to use this tool, so it lacks explicit exclusion guidance.

    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

qrp-mcp MCP server

Copy to your README.md:

Score Badge

qrp-mcp 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/StanimirTenev/qrp-mcp'

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