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Knuckles-Team

vector-mcp

by Knuckles-Team
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

Server Quality Checklist

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

  • Latest release: v2.1.2

  • Disambiguation5/5

    The two tools have clearly distinct purposes: collection management (CRUD operations on collections) and search (semantic, lexical, hybrid). There is no overlap, making it easy for an agent to select the correct tool.

    Naming Consistency5/5

    All tool names follow a consistent 'vector_' prefix pattern with descriptive suffixes ('collection_management', 'search'). Internal action names are uniformly snake_case, maintaining predictability.

    Tool Count3/5

    With only 2 tools, the server feels somewhat thin for a vector database MCP. While each tool bundles multiple actions, a few more tools (e.g., separate tools for document operations) would improve organization.

    Completeness2/5

    The server lacks essential operations such as updating or deleting documents, retrieving collection details, or managing metadata. These gaps would likely cause agent failures in typical workflows.

  • Average 3.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 64 commits in the last 12 weeks
    • Last stable release on
    • 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 provided, so the description carries full burden. It mentions 'delete_collection' as an action but does not disclose that deletion is destructive or irreversible. It also fails to mention authentication requirements, rate limits, or side effects of adding documents.

    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?

    The description is a concise bullet list of actions, front-loading the main purpose. It uses minimal wording and is easy to scan. Every sentence serves a 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?

    Despite high parameter count (14) and no output schema provided (though context says one exists), the description lacks parameter-to-action mappings, usage examples, and behavioral context. It does not explain which parameters are relevant for each action, leaving the agent to rely solely on schema.

    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 baseline is 3. The description lists actions but does not add meaning beyond the schema. Many parameter descriptions (e.g., 'db type', 'host') are vague and not enhanced by the description.

    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 states the tool handles collection management operations and lists four distinct actions with clear names (create_collection, add_documents, delete_collection, list_collections). However, it doesn't explicitly distinguish this tool from its sibling 'vector_search', which may also involve collections.

    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?

    There is no guidance on when to use this tool versus alternatives like vector_search. The description does not specify prerequisites, contexts, or exclude scenarios, leaving the agent to infer usage without support.

    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?

    No annotations are provided, so the description carries full burden. It explains the three search methods but does not disclose whether the tool modifies data, requires authentication, or has rate limits. The read-only nature of search is implicit but not stated. Behavioral transparency is adequate but could be more explicit.

    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?

    The description is relatively concise, with a clear bullet-like listing of actions. The first sentence 'Manage search operations.' is somewhat vague but not overly wordy. Each action is described in one sentence. Minor waste could be trimmed, but overall efficient.

    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?

    With 14 parameters and three distinct actions, the description fails to provide guidance on which parameters are needed for each action (e.g., 'question' likely required for all, connection parameters for external DB). No mention of default behaviors for optional parameters like weights or RRF k. The output schema is present, so return values are covered, but parameter usage across actions is underexplained.

    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%, but parameter descriptions in the schema are minimal (e.g., 'db type', 'host'). The tool description does not add significant meaning beyond the schema—it mentions 'question' but doesn't explain how to use connection parameters or weights. It barely adds value over the schema.

    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 manages search operations and enumerates three distinct search actions: semantic_search, lexical_search, and search. It differentiates from the sibling tool vector_collection_management by focusing on search rather than collection management. The verb 'manage' is a bit generic, but the actions are specific and well-defined.

    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 does not explicitly state when to use this tool versus alternatives. While it lists the three search methods, it offers no guidance on choosing between them or when to avoid this tool. The sibling tool's purpose is implied but not contrasted.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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