Skip to main content
Glama
huangxinping

Huggingface Daily Papers

by huangxinping
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation2/5

    The tools have overlapping purposes with unclear boundaries: get_papers_by_date can retrieve papers for any date, including today and yesterday, making get_today_papers and get_yesterday_papers redundant special cases. This overlap creates ambiguity about which tool to use for date-specific queries, as the descriptions don't clarify when to prefer one over another.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern with clear, descriptive naming: get_papers_by_date, get_today_papers, and get_yesterday_papers. The naming convention is uniform throughout, using snake_case and starting with 'get_' followed by the target, making it predictable and readable.

    Tool Count2/5

    With only 3 tools, the set feels thin and under-scoped for a server named 'Huggingface Daily Papers,' which suggests a broader domain of paper retrieval or analysis. The tools are limited to basic date-based fetching without operations like search, filtering, or metadata access, making the count too low for effective agent use in this context.

    Completeness2/5

    There are significant gaps in the tool surface for the implied domain of accessing HuggingFace papers. Missing operations include searching papers by keyword, filtering by categories or authors, retrieving paper details or abstracts, and accessing trends or summaries. This incompleteness will likely cause agent failures when trying to perform common paper-related tasks beyond simple date retrieval.

  • Average 3.2/5 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
    • 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.

  • 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

  • Behavior2/5

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

    With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool's function but doesn't describe what 'Get' entails (e.g., returns a list, format of papers, pagination, rate limits, or authentication needs). This leaves significant gaps for a tool with no annotation coverage.

    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, efficient sentence with zero waste. It's appropriately sized for a simple tool with one parameter and is front-loaded with the core purpose.

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

    Completeness2/5

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

    Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., list of papers, metadata format) or behavioral aspects like error handling. For a tool with 1 parameter but missing structured output info, this is inadequate.

    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 schema description coverage is 100%, with the parameter 'date' fully documented in the schema (type, format, pattern). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline for high schema coverage.

    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 the action ('Get') and resource ('HuggingFace daily papers') with specific scope ('for a specific date'). It distinguishes from sibling tools by specifying date-based retrieval rather than relative timeframes like 'today' or 'yesterday', though it doesn't explicitly name the siblings.

    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 for date-specific paper retrieval, but doesn't explicitly state when to use this tool versus the sibling tools (get_today_papers, get_yesterday_papers). It provides context about the date parameter but lacks explicit alternatives 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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool fetches papers but doesn't describe traits such as rate limits, authentication needs, data format, or potential errors. This is a significant gap for a tool with zero annotation coverage, making it minimally adequate.

    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, efficient sentence with no wasted words, clearly front-loading the core purpose. It is appropriately sized for a simple tool with no parameters, making it highly concise and well-structured.

    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's low complexity (0 parameters, no output schema, no annotations), the description is complete enough to convey the basic action. However, it lacks details on output format, error handling, or sibling tool differentiation, which are gaps in context for a tool that fetches data, making it minimally viable.

    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 0 parameters, and the input schema coverage is 100% with an empty object. The description doesn't need to add parameter semantics, so it meets the baseline for tools with no parameters, though it doesn't explicitly state the lack of parameters, which slightly limits clarity.

    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 the action ('Get') and resource ('today's HuggingFace daily papers'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_papers_by_date' or 'get_yesterday_papers' beyond the temporal scope implied by 'today's', which prevents a perfect score.

    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 like 'get_papers_by_date' or 'get_yesterday_papers'. It implies usage for today's papers but lacks explicit context, exclusions, or prerequisites, leaving the agent to infer based on tool names alone.

    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?

    With no annotations provided, the description carries full burden but only states what the tool does without disclosing behavioral traits such as rate limits, authentication needs, or response format. It mentions no constraints or side effects, leaving gaps in understanding how the tool behaves.

    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, efficient sentence that directly states the tool's purpose without any wasted words. It is appropriately sized and front-loaded, making it easy to grasp immediately.

    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's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but lacks details on behavioral aspects and sibling differentiation. It covers the basic purpose but doesn't provide enough context for optimal agent use without additional information.

    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 0 parameters with 100% schema description coverage, so the schema fully documents the absence of inputs. The description adds no parameter information, which is acceptable here as there are no parameters to explain, aligning with the baseline for zero parameters.

    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 the action ('Get') and resource ('yesterday's HuggingFace daily papers'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_papers_by_date' or 'get_today_papers' beyond the temporal scope, missing explicit comparison.

    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 like 'get_papers_by_date' or 'get_today_papers'. It implies usage for yesterday's papers only but lacks explicit when/when-not instructions or prerequisites.

    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

huggingface-daily-paper-mcp MCP server

Copy to your README.md:

Score Badge

huggingface-daily-paper-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/huangxinping/huggingface-daily-paper-mcp'

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