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Tar-ive

Grants Search MCP Server

by Tar-ive
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

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'search-grants' has a clear, distinct purpose that cannot be confused with any other tool in the set.

    Naming Consistency5/5

    The single tool name 'search-grants' follows a consistent verb-noun pattern, and with only one tool, there is no inconsistency or deviation to evaluate. The naming is straightforward and predictable.

    Tool Count2/5

    A single tool for a grants search server feels thin and under-scoped. While search is a core function, typical grant-related workflows might include operations like filtering, sorting, or retrieving details, making one tool insufficient for comprehensive coverage.

    Completeness2/5

    The tool set is severely incomplete for a grants search domain. It only provides a basic search function, with obvious gaps such as no ability to view grant details, filter by criteria, or manage saved searches, which are essential for effective agent interaction.

  • Average 2.9/5 across 1 of 1 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 is failing

  • 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 carries the full burden of behavioral disclosure. It mentions searching but doesn't describe behavioral traits such as rate limits, authentication needs, response format, error handling, or whether it's read-only or has side effects. For a search tool with zero annotation coverage, this leaves significant gaps in understanding how it 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 function without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand quickly. Every part of the sentence contributes to clarifying the 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 the complexity of a search tool with no annotations and no output schema, the description is incomplete. It lacks information on behavioral aspects, usage context, and what to expect in return. While the schema covers parameters well, the overall context for effective tool use is insufficient, especially for an agent needing to understand results and limitations.

    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 minimal semantic context beyond the input schema, which has 100% coverage with clear descriptions for all parameters. It implies keyword-based searching but doesn't provide additional details like search scope, result types, or parameter interactions. With high schema coverage, the baseline is 3, as the schema does most of the work.

    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 tool's purpose as 'Search for government grants based on keywords', which includes a specific verb ('Search'), resource ('government grants'), and mechanism ('based on keywords'). It distinguishes the tool's function well, though without sibling tools, differentiation isn't applicable. The purpose is specific and actionable.

    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 limitations. It simply states what the tool does without context about appropriate scenarios or constraints. Since there are no sibling tools, this is less critical, but general usage context is still missing.

    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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