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codeterrayt

Mutual-Funds-Groww-MCP

by codeterrayt
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one for searching/filtering funds and the other for fetching details of a specific fund. There is no overlap or ambiguity in their intended use.

    Naming Consistency5/5

    Both tool names follow the consistent verb_noun pattern in snake_case (search_mutual_funds, fetch_mutual_fund_details). The minor pluralization difference is not enough to break the overall consistent style.

    Tool Count3/5

    With only two tools, the server feels quite thin for a mutual funds domain. While the two tools are essential, the low count suggests a limited scope that may not cover broader investor needs.

    Completeness4/5

    Search and details cover the core discovery and lookup workflow for mutual funds. However, there are minor gaps such as no explicit tool for historical performance or fund comparison, though these could potentially be accessed through search and details.

  • Average 3.7/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 8 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • 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

  • Behavior3/5

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

    No annotations are provided, so the description carries the transparency burden. It indicates a read-only fetch operation and the required search_id, but it does not disclose what 'in-depth details' includes, potential errors, or any behavior beyond the basic retrieval.

    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, focused sentence that front-loads the action ('Fetch in-depth details') and specifies the required input. Every word earns its place; no filler or redundant information.

    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?

    For a simple one-parameter retrieval tool, the description is minimally adequate. It does not explain what 'in-depth details' means or how the output relates to the sibling search tool, but the schema covers the parameter and the operation is clear enough for basic 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 fully describes the single parameter with a clear description and example (e.g., 'axis-silver-fof-regular-growth'). The description's mention of 'search_id' adds no additional semantic value beyond what the schema already provides, so the baseline 3 applies.

    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 fetches in-depth details for a specific mutual fund scheme using a search_id. This distinguishes it from the sibling search_mutual_funds, which presumably returns a list of funds, by focusing on retrieving details for one identified fund.

    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?

    Usage is implied: one would first search mutual funds to obtain a search_id, then call this tool for details. However, the description does not explicitly mention when to prefer this over search_mutual_funds or provide any usage exclusions.

    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?

    With no annotations provided, the description carries the burden of behavioral disclosure. It adds 'real-time' and 'live API endpoint' as useful context, but it does not mention rate limits, pagination behavior, or explicitly state that it is a read-only operation. The non-mutating nature of 'search' is implied, but additional details would strengthen 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 a single, concise sentence that front-loads the core purpose. It contains no fluff and earns its place by conveying both the resource and the live-data characteristic.

    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 tool's complexity (10 parameters) and lack of an output schema, the description is somewhat minimal. It does not explain the return format or pagination behavior, though these are partially evident from the schema. For a search tool, the response is likely a list of funds, but this is not explicitly stated. Overall, the description is adequate but not fully 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 100%, so the schema already documents all 10 parameters with clear descriptions and defaults. The tool description adds no additional parameter-specific meaning, which is acceptable since the schema fully covers semantics. Baseline of 3 is appropriate.

    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 'Search and filter mutual funds in real-time using Groww's live API endpoint' clearly states the action (search and filter), the resource (mutual funds), and the specific context (real-time via Groww's live API). This distinguishes it from the sibling tool 'fetch_mutual_fund_details' by emphasizing search/filter over detail retrieval.

    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 finding and filtering mutual funds but does not explicitly state when to use this tool versus 'fetch_mutual_fund_details'. It lacks direct guidance on alternatives or exclusions, though the purpose is inferable.

    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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