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nestordemeure

ddb-mcp

by nestordemeure
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: search_ddb for searching across the database, get_ddb_snippets for finding query matches within a specific page or issue, and download_ddb_text for downloading OCR text. No overlap in functionality.

    Naming Consistency4/5

    All tool names follow a consistent verb_noun pattern in snake_case. However, 'get' and 'download' are slightly different verbs for similar retrieval actions, causing minor inconsistency.

    Tool Count5/5

    With 3 tools covering search, snippet retrieval, and text download, the count is well-scoped for the domain of accessing digitized newspaper pages. No excess or shortage.

    Completeness4/5

    The tool set supports a complete workflow: search across pages, examine snippets in context, and download full text. Minor gap: no dedicated metadata retrieval tool, but metadata is included in search results.

  • Average 4.5/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 8 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 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.

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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

  • Behavior4/5

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

    With no annotations provided, the description carries the full burden. It discloses caching behavior (refresh parameter), file size advice, and that the tool returns a path to a text file. This adds useful behavioral context beyond a simple 'download' statement.

    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 well-structured with a purpose statement, parameter explanations, and return value note. Every sentence contributes meaningful information without redundancy. It is appropriately sized for the tool's complexity.

    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 that an output schema exists, the description adds useful context about return values (path, file size, read slice advice). The tool has two simple parameters, and the description covers all necessary aspects for correct invocation.

    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 description coverage is 0%, but the description fully compensates by explaining both parameters: identifier format ('ITEMID-pagename' or 'ITEMID') and refresh function. Each parameter's semantics are clearly defined.

    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 downloads OCR text for a page or all pages of an issue. It uses a specific verb ('Download') and resource ('OCR text'), and distinguishes from siblings (get_ddb_snippets and search_ddb) by focusing on full-text download.

    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 implied usage context (use when you need OCR text) but does not explicitly state when to use this tool versus alternatives like get_ddb_snippets or search_ddb. No exclusions or when-not-to-use guidance is given.

    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 provided, the description carries the full burden and clearly indicates a non-destructive read operation by stating 'Find' and 'Returns'. It explains the output format (pages with snippets in {braces}) but does not explicitly mention read-only behavior, which is a minor gap for complete transparency.

    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: one sentence for the purpose, followed by a clear arg/return list. Every sentence adds value without redundancy. It is front-loaded with the core action, making it easy for an agent to quickly grasp the tool's 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's simplicity (two string params, no output schema), the description is complete: it explains what the tool does, how to use the parameters, and what the output looks like. It provides sufficient context for an agent to select and invoke the tool correctly.

    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 schema has 0% description coverage, but the description adds significant meaning: 'identifier' is explained as a page id ('ITEMID-pagename') or issue item id ('ITEMID'), and 'query' is described as a Solr query over page OCR text. This goes well beyond the bare schema types, compensating fully for the lack of 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 finds where a query appears inside one page or one whole issue. It uses a specific verb ('find') and resource ('page' or 'issue'), and distinguishes itself from sibling tools like search_ddb (likely broader search) and download_ddb_text (download full text) by focusing on snippet extraction within a specific identifier.

    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 you have a page or issue identifier and want OCR snippets, but it does not explicitly state when to use this tool versus its siblings. No exclusions or alternatives are mentioned, leaving the agent to infer the context from the tool's specific functionality.

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

  • Behavior5/5

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

    No annotations provided, so description carries full burden. Discloses ordering limitation (cannot sort by date), snippet format (matched terms in braces), and result semantics (total_results as true count). Clearly describes behavioral traits beyond schema.

    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?

    Well-structured with a clear introductory sentence followed by coverage, result format, and parameter details. Slightly verbose but front-loaded with key information. Every section adds 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?

    Given the tool's complexity (8 parameters, no output schema), the description is remarkably complete. Covers purpose, coverage, result format, behavioral quirks, and detailed parameter usage. No significant gaps.

    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 description coverage is 0%, but the description provides extensive parameter details in the Args list, including query syntax (phrases, booleans, wildcards, fuzziness, proximity), and explanations for each field. Fully compensates for missing 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?

    Clearly states the tool searches German newspaper pages in the Deutsches Zeitungsportal. Specifies the resource and action, and implies differentiation from siblings by noting that results include snippets.

    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?

    Provides context on coverage (33.8M pages, densest 1850-1949), result format (pages with snippets), and ordering (relevance only). Offers guidance for chronological work but no explicit when-not-to-use or alternatives.

    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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