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lakshyamehta03

mcp-server-wayback

Server Quality Checklist

67%
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  • Latest release: v0.2.7

  • Disambiguation5/5

    Each tool has a distinct purpose: checking availability, fetching metadata, extracting text, looking up CDX snapshots, searching collections, and searching domains. No overlapping functionality.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun snake_case pattern (e.g., check_availability, get_item_metadata, lookup_snapshots), making them predictable and easy to distinguish.

    Tool Count5/5

    Six tools is appropriate for a Wayback Machine / Internet Archive server, covering the main operations without being overwhelming or too sparse.

    Completeness4/5

    The set covers core read operations (check, get metadata, get content, lookup snapshots, search archive items, search domains). Missing a 'save page' tool and raw HTML retrieval, but covers expected use cases well.

  • Average 3.5/5 across 6 of 6 tools scored. Lowest: 2.9/5.

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

    • No community issues in the last 6 months
    • 1 commit 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.

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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

  • Behavior2/5

    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 of behavioral disclosure. It only states 'Fetch' implying read-only, but does not explicitly declare side effects, rate limits, or other behavioral traits.

    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 with no wasted words. However, it could be slightly more informative without losing conciseness.

    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?

    The description does not explain what the returned metadata includes, and there is no output schema. For a tool that fetches 'rich structured metadata', omitting return format details leaves the agent with incomplete understanding.

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

    Parameters2/5

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

    The description adds minimal semantics to the parameter 'identifier' beyond the schema; it simply says 'by its identifier' without explaining what constitutes a valid identifier or providing examples. With 0% schema description coverage, this is insufficient.

    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 (Fetch), the resource (rich structured metadata of Internet Archive items), and the required input (identifier). It differentiates from sibling tools like search_archive (searching) and check_availability (existence check) by focusing on metadata retrieval for a specific item.

    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 its siblings. No explicit conditions, prerequisites, or alternatives are mentioned, leaving the agent to infer usage context.

    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 cover behavioral traits. It mentions auto-detection of matchType and implies a read-only search, but fails to disclose pagination, error handling, or any constraints. Adequate but with clear gaps.

    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 concise sentence that front-loads the purpose. However, given the number of parameters, it could be slightly more informative without losing conciseness.

    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?

    With five parameters and no schema descriptions, the description is too brief. It does not cover date range filtering, status code filtering, or limit behavior. Although an output schema exists, the description still lacks essential usage context.

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

    Parameters2/5

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

    Schema coverage is 0%, so description must compensate. It only provides a high-level mention of domain/path prefix and auto-detection, without explaining any of the five parameters (e.g., date format, status_code, limit). Minimal compensation.

    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?

    Clearly states it finds archived URLs under a domain or path prefix. Mentions auto-detection of matchType, but does not differentiate from sibling tools like 'search_archive' or 'lookup_snapshots'.

    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?

    Provides no guidance on when to use this tool versus alternatives. No mention of prerequisites or context.

    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, the description carries the full burden. It states the operation fetches and extracts but does not disclose behavioral traits like whether it is read-only, required authorizations, rate limits, or what happens with invalid URLs. The mention of return types (text, word count, metadata) is helpful but 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 a single sentence with two clear parts: the operation and the returns. Every word adds value, with no redundancy. It is front-loaded with the core action.

    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 low complexity (2 params, no output schema), the description covers basic purpose and output but lacks usage guidance, parameter details, and behavioral traits. It is functional but not comprehensive.

    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 0%, so the description must compensate. It adds context that 'url' refers to an archived web page and hints that 'timestamp' specifies a snapshot version. However, it does not elaborate on URL format, timestamp syntax, or constraints, so value is moderate.

    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 'Fetch and extract text content' and the resource 'archived web page', and lists return values. It effectively distinguishes from sibling tools like 'check_availability' or 'get_item_metadata' which 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 Guidelines3/5

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

    The description implies usage for extracting text from a specific snapshot but provides no explicit guidance on when to use this tool versus alternatives like 'lookup_snapshots' or 'search_archive'. No when-not-to-use or prerequisites are mentioned.

    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?

    The description indicates a read-only operation (checking and returning) but does not elaborate on edge cases (e.g., what happens if no snapshot exists, or how 'closest' is determined). Since no annotations are present, the description carries the full burden of behavioral disclosure but falls short of being fully transparent.

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

    Conciseness5/5

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

    The description is a single sentence of 15 words, efficiently conveying the core purpose without any filler. It is front-loaded with the action ('Check if a URL has been archived') and immediately states the return value.

    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 no output schema, the description should hint at the return structure (e.g., snapshot metadata) and possible error cases. It only says 'return the closest snapshot', which is vague. For a simple tool this is adequate but not fully informative for an agent.

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

    Parameters2/5

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

    With 0% schema description coverage, the description must compensate. It clarifies that 'url' is the URL to check and that 'timestamp' is optional but does not explain its role (e.g., that it is used to find the closest snapshot to that time). This leaves ambiguity about the timestamp parameter's meaning and usage.

    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 verb 'Check if a URL has been archived' and the resource 'the Wayback Machine', with the outcome 'return the closest snapshot'. This differentiates it from siblings like lookup_snapshots (which would return multiple snapshots) and get_snapshot_content (which retrieves a specific snapshot's content).

    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 checking availability of a URL, but it does not explicitly say when to use it versus siblings like lookup_snapshots or search_archive. No when-not or alternative guidance is provided, so an agent may not know the best tool for different scenarios.

    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?

    Without annotations, the description discloses default collapse behavior, limit consumption, and the constraint that latest cannot combine with date range, offering good behavioral insight.

    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 front-loaded with the main purpose and structured with clear sections, though slightly lengthy; each sentence is informative.

    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 no output schema or annotations, the description covers main purpose, key behaviors, and important parameters, though it lacks output format or error handling details.

    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 description adds significant value for collapse and latest parameters with detailed examples, but covers other parameters only in passing, partially compensating for 0% schema description 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 tool returns CDX snapshots for a URL with optional date range and status-code filters, differentiating it from sibling tools like get_snapshot_content.

    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 explains when to use different collapse options and the latest parameter, providing context for choosing among them, but does not explicitly compare to sibling tools.

    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?

    Discloses it returns only uploaded discrete items, not web pages. Mentions Lucene fields. No annotations provided, so description carries burden; it is mostly transparent, but lacks info on rate limits or authentication.

    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, uses bullet points for negative usage and good uses, no wasted words.

    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?

    Good overview but lacks details on parameter usage, pagination, or output structure. Output schema exists but is not described; parameter details are missing for effective use.

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

    Parameters2/5

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

    Schema description coverage is 0%. The description does not elaborate on query syntax, mediatype, year_from, year_to, or limit parameters, relying solely on parameter names.

    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 searches Internet Archive collections using Lucene syntax, distinguishes from Wayback Machine search, and lists good uses.

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

    Usage Guidelines5/5

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

    Explicitly lists what NOT to use for (news, government circulars, Wikipedia, web crawl) and suggests alternative tools like search_domain and lookup_snapshots.

    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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