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1818TusculumSt

Fabric MCP Server

by 1818TusculumSt
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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

    Each tool targets a distinct action: apply a pattern, get its details, list all patterns, and update the pattern list. No overlaps or ambiguity.

    Naming Consistency5/5

    All tools follow a consistent verb_noun snake_case pattern (apply, get, list, update), making them predictable and easy to use.

    Tool Count5/5

    With only 4 tools, the set is well-scoped for the specific domain of managing and applying Fabric patterns, neither too sparse nor too heavy.

    Completeness5/5

    The tool surface covers the core lifecycle of Fabric patterns: listing, retrieving details, applying, and refreshing the list. No obvious gaps for the stated purpose.

  • Average 3.7/5 across 4 of 4 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

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  • 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?

    No annotations; description only says 'apply' without mentioning side effects, auth, or output behavior. Minimal transparency for a transformation 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?

    Two sentences, front-loaded with purpose and examples. No wasted words.

    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?

    Adequate for a tool with full enum and 2 parameters, but lacks output description and error handling. Could be more complete given no output 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 coverage is 100%, so baseline 3. Description adds listing of pattern examples and clarifies input_text purpose, but adds marginal value beyond 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 applies Fabric AI patterns to input text, with specific examples. It distinguishes from siblings: get, list, update.

    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?

    Implied usage for processing text with a pattern, but no explicit when-not-to-use or comparison with alternatives like get_fabric_pattern or list_fabric_patterns.

    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?

    Without annotations, the description should disclose behavioral traits like read-only nature or response format. It only states the function, omitting any side effects, permissions, or output details.

    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 sentence with no superfluous words. It is appropriately concise for a simple retrieval tool.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the low complexity (1 param, no output schema), the description is sufficient to convey the tool's purpose, though it could mention that no modifications occur.

    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 coverage is 100% with a single 'pattern' parameter having an enum. The description adds no extra meaning beyond the schema, so baseline 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 clearly states the action 'Get' and the resource 'full prompt/instructions for a specific Fabric pattern'. This distinguishes it from sibling tools like apply_fabric_pattern (apply) and list_fabric_patterns (list).

    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?

    No explicit guidance is provided on when to use this tool versus its siblings. The sibling names hint at different purposes, but the description lacks a direct comparison or usage context.

    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 does not mention behavioral traits such as read-only nature, pagination, or result limits. For a simple listing, this is adequate but lacks depth.

    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, front-loaded sentence that directly states the tool's purpose without any unnecessary words or repetition.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness4/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given the simplicity of the tool (one optional parameter, no output schema), the description is sufficient to understand its basic function. However, it could hint at the return format or that results are a list of pattern objects with descriptions.

    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 tool description does not add information about the 'filter' parameter beyond what the input schema already provides (including examples). Since schema coverage is 100%, baseline is 3; no extra meaning is added.

    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 'List all available Fabric patterns with their descriptions', specifying the verb (list) and resource (Fabric patterns). This distinguishes it from siblings like get_fabric_pattern (single pattern) and apply_fabric_pattern (action).

    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 use for browsing all patterns but does not explicitly state when to use this tool versus alternatives like get_fabric_pattern for a specific pattern, or when filtering might be beneficial. No when-not guidance is provided.

    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?

    No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only says 'Force an update,' which hints at a potentially destructive or blocking operation, but lacks details on side effects, permissions, or expected behavior (e.g., network call, latency).

    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 sentence that immediately states the action and purpose. It is front-loaded and contains no extraneous 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 tool with no parameters, no output schema, and a simple action, the description is minimally adequate. However, it lacks details on what 'force an update' entails and does not set expectations for the agent (e.g., success indication, potential delays).

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters4/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    There are no parameters in the input schema, so the description cannot add meaning beyond the schema. With 100% schema coverage and zero parameters, a baseline score of 4 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 clearly states the tool's action ('Force an update of the pattern list from GitHub') and its purpose ('get the latest patterns immediately'). It distinguishes from sibling tools which are about applying, getting, or listing patterns.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description advises using it to get the latest patterns immediately, which gives clear usage context. However, it does not mention when not to use it or alternatives, though the sibling names imply differentiation.

    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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