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Server Quality Checklist

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  • Disambiguation5/5

    Each tool has a distinct purpose with clear boundaries: build vs. run (with launch), inspection vs. screenshot, and tap vs. type. No overlapping functionality causes confusion.

    Naming Consistency5/5

    Perfect consistency using {domain}_{action} pattern throughout. All use snake_case with simulator_* prefix for simulator tools and xcode_* prefix for build tools.

    Tool Count5/5

    Six tools is ideal for this focused scope covering Xcode build automation and iOS Simulator UI interaction. No bloat, no missing essentials for the core workflow.

    Completeness4/5

    Covers the primary iOS development loop (build, run, inspect, interact) well. Minor gaps exist for advanced UI automation (swipe gestures, hardware button simulation, app termination) but core functionality is solid.

  • Average 3.7/5 across 5 of 6 tools scored.

    See the tool scores section below for per-tool breakdowns.

  • This repository includes a README.md file.

  • This repository includes a LICENSE file.

  • Latest release: v0.1.0

  • 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.

  • This repository includes a glama.json configuration file.

  • This server provides 6 tools. View schema
  • No known security issues or vulnerabilities reported.

    Report a security issue

  • This server has been verified by its author.

  • Add related servers to improve discoverability.

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 successfully discloses the return structure (file, line, column, severity, message) since no output schema exists. However, it omits other critical behavioral traits: whether builds are destructive to previous artifacts, execution time expectations, or prerequisite requirements (Xcode installation).

    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 consists of two efficient sentences with zero waste. It is front-loaded with the core action ('Build...') followed by return value details. Every sentence earns its place.

    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 4 parameters (1 required), no annotations, and no output schema, the description adequately covers the core function and return format. However, gaps remain in usage guidelines (vs. xcode_run) and behavioral transparency (side effects, idempotency), preventing a higher score.

    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?

    With 100% schema description coverage, the baseline is 3. The description reinforces the project_path semantics by mentioning 'project or workspace,' but adds no further syntax details, format examples, or constraints beyond what the schema already provides for the four parameters.

    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 tool 'Build[s] an Xcode project or workspace' with a specific verb and resource. It implicitly distinguishes from simulator_* siblings (which interact with simulators) and xcode_run (execution vs. compilation), though it does not explicitly name siblings to differentiate.

    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 implies usage by noting it returns diagnostics for errors/warnings, suggesting use for compilation verification. However, it lacks explicit when-to-use guidance or comparison with xcode_run (e.g., 'use this to compile before running').

    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 full burden. It successfully discloses the external dependency (idb) and implies coordinate-based interaction, but fails to describe return values, error behaviors (e.g., out-of-bounds coordinates), or whether the operation is synchronous.

    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 states the action immediately, and the second provides essential prerequisite information. Perfectly front-loaded and appropriately sized for the tool's complexity.

    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 4-parameter interaction tool with no output schema or annotations, the description covers the core function and dependency but lacks completeness regarding the coordinate system origin (0,0 location), return value structure, and error scenarios.

    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?

    Input schema has 100% description coverage, establishing a baseline of 3. The description mentions 'specific coordinates' which aligns with the x/y parameters, but adds no semantic detail beyond what the schema already provides regarding the duration or simulator_udid parameters.

    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 specific action ('Tap') and target resource ('iOS Simulator screen'), distinguishing it effectively from siblings like simulator_screenshot (capture), simulator_type (text input), and xcode_build (compilation).

    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 provides critical prerequisite information ('Requires idb') but lacks explicit guidance on when to use this tool versus alternatives like simulator_type, or when tapping is preferable to other interaction methods.

    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 full burden. It discloses the external idb dependency and implies statefulness ('currently focused field'), but omits error handling, idempotency, or timing behavior.

    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: first states the action, second states the prerequisite. Information is front-loaded and appropriately scoped.

    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 2-parameter tool with no output schema, covering the core action and dependency. However, gaps remain regarding failure modes (what if no field is focused?) and synchronous/asynchronous behavior.

    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?

    Input schema has 100% description coverage ('Simulator UDID', 'Text to type'), establishing baseline 3. The description adds no parameter-specific semantics beyond what the schema already provides.

    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 specific action ('Type text') and target ('currently focused field on the iOS Simulator'), distinguishing it from sibling tools like simulator_tap (gestures) and simulator_screenshot (visual capture).

    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?

    Provides critical prerequisite information ('Requires idb') but lacks explicit guidance on when to use this versus simulator_tap (e.g., 'use after focusing a field') or error conditions if no field is focused.

    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 full burden. It discloses output behavior (build errors vs. success message with process ID) and the dual build-then-launch sequence. However, it omits operational details like whether the call blocks until completion, simulator boot behavior, or timeout characteristics.

    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: first states the action (build + launch), second states the return values. Every word earns its place, and critical information is front-loaded. Appropriate length for the tool's complexity.

    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 5-parameter tool with no output schema, the description compensates by explaining return values (build errors, process ID) and clarifying the compound operation. It adequately covers the tool's behavior, though it could improve by mentioning whether the simulator is auto-booted or if the operation is synchronous.

    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 input schema has 100% description coverage, documenting all five parameters including defaults. The description mentions 'iOS Simulator' and 'build' which contextually anchors the parameters, but adds no specific syntax, format details, or parameter interdependencies beyond what the schema already provides. Baseline 3 is appropriate given the comprehensive 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 explicitly states the dual action ('Build... and launch') and identifies the specific resources (Xcode project, iOS Simulator). It effectively distinguishes from sibling tool 'xcode_build' (build-only) and simulator interaction tools by specifying it both compiles and deploys the app.

    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 explains what happens on success or failure (returns build errors or process ID), providing implicit usage context. However, it lacks explicit guidance on when to use this versus 'xcode_build' (e.g., 'use this when you need to test the app interactively') or prerequisites like requiring Xcode command line tools.

    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 full burden. It successfully discloses the external dependency (idb) and output format (JSON), but lacks disclosure of read-only safety, error conditions (e.g., simulator not running), or the structure of the returned accessibility tree.

    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?

    Three sentences with zero waste: first defines the core function, second explains the value proposition, third states the hard prerequisite. Perfectly front-loaded and appropriately sized for the tool's complexity.

    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 single-parameter inspection tool, but lacks description of the JSON output structure since no output schema exists. Given the domain-specific nature of 'accessibility tree,' some description of the returned hierarchy or element properties would strengthen agent effectiveness.

    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%, fully documenting the simulator_udid parameter including its default behavior. The description does not explicitly discuss parameters, but the schema is self-sufficient, making the baseline score of 3 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 specific action (Get), resource (accessibility tree), format (JSON), and scope (current iOS Simulator screen). It effectively distinguishes from siblings like simulator_screenshot (visual) and simulator_tap/type (interaction) by emphasizing UI element discovery.

    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?

    Provides valuable prerequisite information ('Requires idb') and contextual usage guidance ('Useful for finding UI elements to interact with'), implying it should be used before tap/type operations. Could be improved by explicitly contrasting with simulator_screenshot for debugging strategies.

    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?

    No annotations provided, so description carries full burden. It successfully discloses the critical behavioral trait of return format ('base64-encoded PNG') compensating for the missing output schema. Could mention whether this affects simulator state (it shouldn't) or requires specific permissions.

    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, zero waste. First sentence states the action, second discloses return format. Perfectly front-loaded with no filler.

    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?

    Appropriately complete for a simple single-parameter tool. The description compensates for missing output schema by specifying the base64 PNG return format. Minor gap: doesn't specify error behavior if no simulator is booted.

    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%, establishing baseline 3. The description does not add parameter-specific semantics beyond the schema, but the schema already adequately documents the optional simulator_udid parameter with its default behavior.

    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?

    Clear specific verb ('Capture') + resource ('screenshot of the iOS Simulator screen'). Unambiguously distinguishes from siblings: unlike simulator_describe (metadata), simulator_tap/type (interactions), or xcode_build/run (compilation/execution), this tool specifically captures visual state.

    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 by the action (use when visual verification needed), but lacks explicit when-to-use guidance versus alternatives like simulator_describe, or prerequisites such as requiring a booted simulator.

    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.

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How to claim the server?

If you are the author of the server, you simply need to authenticate using GitHub.

However, if the MCP server belongs to an organization, you need to first add glama.json to the root of your repository.

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

Then, authenticate using GitHub.

Browse examples.

How to make a release?

A "release" on Glama is not the same as a GitHub release. To create a Glama release:

  1. Claim the server if you haven't already.
  2. Go to the Dockerfile admin page, configure the build spec, and click Deploy.
  3. Once the build test succeeds, click Make Release, enter a version, and publish.

This process allows Glama to run security checks on your server and enables users to deploy it.

How to add a LICENSE?

Please follow the instructions in the GitHub documentation.

Once GitHub recognizes the license, the system will automatically detect it within a few hours.

If the license does not appear on the server after some time, you can manually trigger a new scan using the MCP server admin interface.

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.

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