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BACH-AI-Tools

Truecaller Data2 MCP Server

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 single tool 'search' has a distinct and clear purpose for searching Truecaller data, so agents cannot misselect between multiple options.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name 'search' follows a simple verb pattern, and there are no other tools to compare it against for inconsistency.

    Tool Count2/5

    A single tool is too few for a server named 'Truecaller Data2 MCP Server', which suggests a broader data-related scope. This minimal set limits functionality and likely leaves significant gaps in handling Truecaller data operations, making it inappropriate for comprehensive use.

    Completeness1/5

    The tool set is severely incomplete for the implied domain of Truecaller data. With only a search tool, there are obvious gaps such as creating, updating, deleting, or retrieving specific data entries, which are essential for full CRUD/lifecycle coverage in a data server.

  • Average 2.4/5 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 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 carries full burden for behavioral disclosure. 'Truecaller Search' implies a lookup operation that might involve external services, but it doesn't disclose any behavioral traits like rate limits, authentication requirements, privacy implications, or what happens with invalid inputs. The description is too minimal to provide meaningful transparency beyond the basic action implied by 'Search'.

    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 with just two words, 'Truecaller Search'. It's front-loaded and wastes no space, though this conciseness comes at the cost of clarity. Every word earns its place by at least hinting at the tool's domain (Truecaller) and action (Search).

    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 tool has no annotations, no output schema, and a simple input schema with one parameter, the description is incomplete. It doesn't explain what the tool does beyond the vague 'Search', what results to expect, or any behavioral context. For a tool that likely interacts with an external service (Truecaller), more information about its purpose and output would be needed for adequate completeness.

    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 100%, with the parameter 'number' documented as requiring a string like '919999999999'. The description adds no additional meaning about parameters beyond what the schema provides. According to the rules, with high schema coverage (>80%), the baseline score is 3 when no param info is in the description, which applies here.

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

    Purpose2/5

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

    The description 'Truecaller Search' restates the tool name 'search' with a brand modifier, making it essentially tautological. It doesn't specify what resource is being searched (phone numbers? contacts? databases?) or what action is performed (lookup? verify? identify?). While 'Search' implies a lookup operation, the lack of specificity about what is being searched and what results are returned makes this vague.

    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?

    No guidance is provided about when to use this tool. There are no sibling tools mentioned, so no alternative comparisons are needed, but the description doesn't indicate any context, prerequisites, or constraints for usage. The agent must infer usage from the parameter name 'number' alone, which is insufficient guidance.

    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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