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automatikstudio

LegalForge MCP Server

by automatikstudio
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JavaScript
Remote

Server Quality Checklist

50%
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 'generate_legal_document' has a clear and distinct purpose.

    Naming Consistency5/5

    Since there is only one tool, naming consistency is inherently perfect. The tool name follows a clear verb_noun pattern (generate_legal_document).

    Tool Count2/5

    A single tool is too few for a server named 'LegalForge MCP Server', which suggests a broader legal domain. This feels thin and incomplete for generating legal documents, as it lacks supporting tools like editing, reviewing, or managing templates.

    Completeness2/5

    The tool surface is severely incomplete for legal document generation. While 'generate_legal_document' covers creation, there are obvious gaps such as updating, deleting, listing, or customizing documents, which are essential for a full workflow.

  • Average 2.9/5 across 1 of 1 tools scored.

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

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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?

    With no annotations provided, the description carries full burden for behavioral disclosure. It mentions AI generation but lacks critical details: whether documents are legally binding, if review by a lawyer is recommended, potential rate limits, or what the output format looks like. For a legal document generation tool, this is a significant gap in 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, efficient sentence that clearly states the tool's purpose with relevant examples. It's appropriately sized and front-loaded with zero wasted words, making it easy for an agent to parse quickly.

    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 legal document generation, no annotations, and no output schema, the description is insufficient. It doesn't address the nature of the output (e.g., plain text, formatted document), legal disclaimers, or important behavioral constraints. The description leaves too many unanswered questions for a tool of this nature.

    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 parameters thoroughly. The description adds no additional parameter semantics beyond what's in the schema. According to scoring rules, when schema coverage is high (>80%), the baseline is 3 even with no param info in 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 clearly states the verb ('generate') and resource ('professional legal documents') with specific examples (Privacy Policy, Terms of Service, Cookie Policy). 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 constraints. It simply states what the tool does without context for application. This lack of usage context leaves the agent without direction on appropriate scenarios.

    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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  • Evaluate tool definition quality.

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