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AnuragRai017

Database Updater MCP Server

by AnuragRai017
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JavaScript
Hybrid

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have completely distinct purposes with no overlap: create_note is for creating a new note, while update_database is for updating a database from a file. An agent can easily tell them apart based on their different functions and target resources (note vs. database).

    Naming Consistency2/5

    The naming is inconsistent: create_note follows a verb_noun pattern, but update_database uses a verb_noun pattern with a different verb style (update vs. create) and lacks a clear object for the update action. While both are readable, they do not follow a predictable or uniform convention across the set.

    Tool Count2/5

    With only 2 tools, this server feels thin for a 'Database Updater' purpose. The scope suggests operations like querying, deleting, or managing database entries, but only update_database directly relates, while create_note seems out of place. This mismatch makes the count inappropriate for the apparent domain.

    Completeness2/5

    The tool surface is significantly incomplete for a database updater server. There are no tools for reading, deleting, or querying the database, and create_note does not align with the core domain. This leaves obvious gaps that will hinder agents in performing typical database operations.

  • Average 2.8/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 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 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.

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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?

    With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Create a new note', implying a write operation, but does not disclose any behavioral traits like permissions needed, whether the creation is idempotent, error handling, or response format. This leaves significant gaps for a mutation tool.

    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 'Create a new note' is extremely concise and front-loaded, consisting of a single, direct sentence with no wasted words. It efficiently communicates the core action without unnecessary elaboration.

    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 that this is a mutation tool with no annotations and no output schema, the description is incomplete. It does not address behavioral aspects like what happens on success or failure, nor does it provide context for usage relative to siblings. The 100% schema coverage helps with parameters, but overall completeness is lacking for effective tool invocation.

    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 input schema has 100% description coverage, with clear documentation for 'title' and 'content' parameters. The description does not add any semantic details beyond what the schema provides, such as format constraints or examples. Baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'Create a new note' clearly states the action (create) and resource (note), making the purpose understandable. However, it lacks specificity about what a 'note' entails in this context and does not distinguish it from sibling tools like 'update_database', which could involve similar data operations.

    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, such as the sibling tool 'update_database'. It does not mention prerequisites, context for creation, or any exclusions, leaving the agent without usage instructions.

    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 updates a database, implying a mutation operation, but fails to describe critical behaviors such as required permissions, whether the update is destructive or additive, error handling, or any rate limits. This is a significant gap for a tool that performs database writes.

    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 unnecessary words. It is front-loaded with the core action and resource, making it easy to parse. Every part of the sentence contributes essential information, earning its place.

    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 the complexity of a database update tool with no annotations and no output schema, the description is incomplete. It lacks details on the update behavior (e.g., whether it overwrites or merges data), expected outcomes, error conditions, or security considerations. This leaves the agent with insufficient context for safe and effective use.

    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%, so the input schema already documents all four parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining how parameters interact or providing examples. This meets the baseline for high schema coverage but doesn't enhance parameter understanding.

    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 ('Update') and resource ('the database'), specifying the source format ('from a CSV or Excel file'). It distinguishes from the sibling tool 'create_note' by focusing on database operations rather than note creation. However, it doesn't specify what 'update' entails (e.g., insert, upsert, replace), keeping it from 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, prerequisites, or exclusions. It mentions the source file types but doesn't explain when this tool is appropriate compared to other database operations or data import methods. This lack of context leaves the agent with minimal usage direction.

    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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