Skip to main content
Glama
FixtureForge

SeedWeaver

by FixtureForge
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Local

Server Quality Checklist

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

  • Latest release: v0.2.0

  • Disambiguation5/5

    The two tools have entirely distinct purposes: one for analyzing/validating schema understanding, the other for generating data. No overlap or ambiguity.

    Naming Consistency5/5

    Both tools follow the consistent verb_noun pattern (analyze_schema, generate_seed_data), making their actions and targets clear.

    Tool Count3/5

    With only 2 tools, the server is minimal but still covers its core purpose. It could benefit from a few more tools (e.g., configuration, validation), but the count is acceptable for a focused utility.

    Completeness4/5

    The tool surface covers the essential workflow: analyze schema, then generate data. Minor gaps like customizing data types or revalidating are absent but not critical for the stated purpose.

  • Average 4.3/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 5 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

  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 full burden. It states the tool parses and reports, implying read-only behavior, but does not explicitly mention lack of side effects, authentication needs, or rate limits. The output content is described at a high level.

    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 with zero waste. The first sentence concisely states the action and scope, the second provides clear usage guidance.

    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 one parameter with good schema coverage and no output schema, the description outlines what the tool outputs (tables, columns, relationships, seed order) but lacks details on the return format or structure. It is mostly complete for a simple analysis tool.

    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?

    Schema description coverage is 100% for the single parameter, and the description adds context about acceptable formats (SQL DDL or JSON schema with 'tables' array), which is already in the schema. The description also explains what the tool reports, which goes beyond the parameter 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 parses a database schema and reports tables, columns, relationships, and seed data order. It distinguishes from the sibling tool 'generate_seed_data' by noting it is used first to confirm understanding.

    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 explicitly says 'Use this first to confirm SeedWeaver understands the schema correctly,' indicating it should precede generate_seed_data. However, it does not discuss when not to use it or provide alternatives beyond the implied sequence.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    Without annotations, the description bears full burden for behavioral disclosure. It effectively communicates key behaviors: generating realistic data, respecting constraints, and supporting multiple output formats. It also notes Pro features (seed, CSV). However, it does not discuss error handling or limitations.

    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 highly concise, comprising three focused sentences. It front-loads the primary purpose, then explains features, and finally specifies input/output options. No wasted words.

    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?

    For a tool with 4 parameters (100% schema coverage) and no output schema, the description provides sufficient context: input types, output formats, and core behavioral guarantees. It lacks mention of error conditions but is otherwise complete for its intended use case.

    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?

    Schema coverage is 100%, providing detailed parameter descriptions. The tool description adds value by noting defaults (rows=10), Pro features (seed, CSV), and the schema input format. This extra context elevates the score above baseline 3.

    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 purpose: generating realistic, referentially-coherent test data. It specifies key features (foreign key resolution, unique constraints, realistic values) and distinguishes itself from the sibling tool 'analyze_schema' by focusing on data generation.

    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 explains when to use the tool (generating test data from a schema) and mentions input options (SQL DDL or JSON schema) and output formats. However, it does not explicitly state when not to use it or provide direct comparison with the sibling tool, leaving some ambiguity.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

seedweaver-mcp MCP server

Copy to your README.md:

Score Badge

seedweaver-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/FixtureForge/seedweaver-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server