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07freedom

M-Team MCP Server

by 07freedom
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.1

  • Disambiguation5/5

    Each tool serves a unique purpose: search finds torrents, detail retrieves information, and download fetches the torrent file. No overlap or ambiguity exists.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (download_torrent, get_torrent_detail, search_torrents), making it predictable for agents.

    Tool Count4/5

    With 3 tools, the set is small but covers essential torrent operations (search, detail, download). Slightly under for full lifecycle but reasonable for a basic client.

    Completeness3/5

    The tools cover searching, viewing details, and downloading torrents, but miss uploads, deletions, or seed management. Notable gaps exist for a complete torrent management server.

  • Average 4.2/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 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.

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

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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, so description carries burden. Lists return fields (name, size, etc.) indicating read-only behavior, but doesn't disclose error handling, permissions, or rate limits. Adequate but not rich.

    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?

    Concise, front-loaded purpose, clear Args/Returns structure. Every sentence adds value.

    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?

    Complete for a simple one-param read tool with no annotations: covers purpose, parameter, return. Lacks error info but acceptable for given complexity.

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

    Parameters5/5

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

    Schema coverage is 0%, but description adds full meaning: param is numeric ID, with example and explanation. Alone it fully documents the parameter.

    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?

    Clearly states it retrieves detailed info for a specific torrent by ID, with a specific verb and resource. Distinguishes from siblings (search_torrents, download_torrent) by focusing on detail retrieval.

    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?

    Implies use when you have a torrent ID via 'by its ID' and example, but no explicit when-not or alternatives. Context is clear but lacks exclusions.

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

  • Behavior3/5

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

    No annotations are provided, so the description must carry the full burden. It describes parameters, return format, and the search action, which is inherently read-only. However, it does not explicitly state that it is non-destructive, nor does it mention any potential side effects, auth requirements, or rate limits. The transparency is adequate but not exceptional.

    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 concise and well-structured with a one-line summary followed by clear Args and Returns sections. Every sentence adds value; there is no redundant or missing information. It is appropriately sized and front-loaded with the core purpose.

    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?

    Given the tool has 4 parameters, no annotations, but an output schema, the description covers all necessary aspects: the search context (M-Team), parameter details, and return format (listing IDs, names, sizes, etc.). It is complete enough for an agent to use correctly, and the output schema is leveraged by describing the return value.

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

    Parameters5/5

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

    The input schema has 0% description coverage, but the description fully compensates by explaining each parameter: keyword supports Chinese/English, mode lists all allowed values (including default), page_number and page_size have defaults and max for page_size. This adds significant meaning beyond the raw schema types and defaults.

    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 'Search torrents on M-Team by keyword', specifying the verb (search), resource (torrents on M-Team), and key parameter (keyword). It distinguishes itself from sibling tools like download_torrent (download) and get_torrent_detail (get detail of a single torrent), making it unambiguous.

    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 does not explicitly state when to use this tool versus alternatives. It implies usage through the name and siblings, but lacks explicit guidance like 'Use for searching; use download_torrent for downloading'. The usage context is inferred, not stated.

    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?

    The description reveals internal steps (token acquisition, file save) and return value (path or error). It does not mention permissions or side effects, but for a download tool, this is adequate. No annotations are present, so description carries the full burden.

    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 concise with a clear header and structured details (Args, Returns). It is front-loaded with the main action. Slightly verbose in explaining process, but overall efficient.

    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 one parameter, no annotations, and an existing output schema, the description covers the tool's purpose, process, parameter, and return value. It could include more on error handling, but it is sufficiently complete for this simple tool.

    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 single parameter 'torrent_id' has no schema description, but the description adds meaning by specifying it is numeric and giving an example ('1125330'). This compensates for the 0% schema coverage.

    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 action 'Download a .torrent file for the given torrent ID,' which is a specific verb and resource. It distinguishes from siblings 'get_torrent_detail' and 'search_torrents' as these serve different purposes.

    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 outlines the process (obtain token, download, save to directory) and implies use for downloading torrent files. It does not explicitly state when not to use or alternatives, but the context is clear enough.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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