MCP Tauri Automation
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose with no significant overlap. The tools cover different aspects of Tauri automation: launching/closing apps, UI interaction (clicking, typing, waiting), element inspection, screenshot capture, and command execution. The descriptions make it easy to distinguish between similar tools like click_element and wait_for_element.
Naming Consistency5/5All tools follow a consistent verb_noun naming pattern with snake_case throughout. The naming is predictable and readable: capture_screenshot, click_element, close_app, execute_tauri_command, get_app_state, get_element_text, launch_app, type_text, wait_for_element. There are no deviations in naming conventions.
Tool Count5/5With 9 tools, this is well-scoped for Tauri automation. Each tool earns its place by covering essential operations: app lifecycle management, UI interaction, element inspection, and command execution. The count is neither too sparse nor bloated, providing comprehensive coverage without redundancy.
Completeness4/5The tool set provides excellent coverage for core Tauri automation workflows including app control, UI interaction, and state inspection. Minor gaps exist such as no explicit tool for navigating between pages/windows or handling file operations, but agents can work around these using existing tools like execute_tauri_command for extended functionality.
Average 3.3/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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.jsonto 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
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool executes a command but lacks details on permissions needed, error handling, side effects (e.g., if it modifies app state), or response format. This is a significant gap for a command execution tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. However, it could be slightly more front-loaded by explicitly mentioning it's for IPC commands in Tauri apps upfront, though it's already quite concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of executing IPC commands, no annotations, and no output schema, the description is incomplete. It fails to cover behavioral aspects like safety, error cases, or return values, which are crucial for an agent to use this tool effectively in a Tauri context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, so the schema already documents both parameters ('command' and 'args'). The description adds no additional meaning beyond what the schema provides, such as examples of valid commands or argument structures, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Execute a Tauri IPC command') and specifies the target resource ('Tauri app's src-tauri/src/main.rs file'), making the purpose unambiguous. However, it doesn't explicitly differentiate this tool from its siblings (like 'get_app_state' or 'launch_app'), which would require a 5.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, such as other IPC-related tools or its siblings (e.g., 'get_app_state' for reading state vs. this for executing commands). It mentions the command must be exposed in a specific file, but this is a prerequisite rather than usage context.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure but offers minimal information. It implies a write operation ('type text') but doesn't cover critical aspects like error handling (e.g., if selector fails), side effects (e.g., focus changes), or performance considerations (e.g., typing speed).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core purpose and appropriately sized for a straightforward tool, earning full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (interactive UI operation) and lack of annotations or output schema, the description is incomplete. It doesn't explain return values (e.g., success/failure), error conditions, or dependencies (e.g., requires an active app context), leaving significant gaps for an agent to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents all parameters (selector, text, clear). The description adds no additional meaning beyond what's in the schema, such as examples of valid selectors or when to use the 'clear' option. Baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('type text') and target ('into an input field or editable element'), providing a specific verb+resource combination. However, it doesn't differentiate from potential sibling tools like 'click_element' or 'get_element_text' that might also interact with input fields, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. It doesn't mention prerequisites (e.g., element must be visible/editable), exclusions (e.g., not for read-only elements), or comparisons with sibling tools like 'click_element' for interaction or 'get_element_text' for reading.
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?
With no annotations provided, the description carries full burden for behavioral disclosure. While 'Get' implies a read operation, it doesn't specify whether this tool requires the element to be visible/loaded, what happens if the selector matches multiple elements, error behavior for non-existent elements, or performance characteristics. The description adds minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any unnecessary words. It's perfectly front-loaded with the core functionality immediately apparent. Every word earns its place in this minimal description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter read operation with no output schema, the description provides the basic purpose but lacks important context. It doesn't explain what format the text is returned in (plain text, HTML, trimmed), whether whitespace is normalized, or what happens with nested elements. The description is minimally adequate but leaves significant gaps in understanding the tool's behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the selector parameter fully documented in the schema. The description doesn't add any parameter-specific information beyond what's already in the schema. This meets the baseline score of 3 when schema coverage is high and no additional parameter semantics are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Get' and the resource 'text content of an element', making the purpose immediately understandable. However, it doesn't distinguish this tool from potential siblings like 'get_app_state' or 'wait_for_element' that might also retrieve text-related information in different contexts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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. With siblings like 'capture_screenshot' (visual capture) and 'wait_for_element' (timing-based), there's no indication whether this tool should be used for immediate text extraction versus waiting for elements to appear or capturing text via screenshots.
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?
With no annotations, the description carries full burden but provides minimal behavioral context. It doesn't mention whether this requires the app to be launched first, what happens if the element isn't found (e.g., error behavior), or if it waits for the element to be clickable. This leaves critical gaps for a UI automation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero wasted words. It's front-loaded with the core action and uses clear, direct language appropriate for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a UI interaction tool with no annotations and no output schema, the description is incomplete. It lacks context about prerequisites (e.g., app must be launched), error handling, or what constitutes success, which are essential for reliable use alongside siblings like launch_app or wait_for_element.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the schema fully documenting the single parameter's type, requirement, and examples. The description adds no additional parameter semantics beyond what's in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('Click') and target ('a UI element identified by a CSS selector'), distinguishing it from siblings like type_text (typing) or get_element_text (reading). It uses precise terminology that directly maps to the tool's function.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like execute_tauri_command (which might handle clicks differently) or wait_for_element (which might be a prerequisite). The description only states what it does, not when it's appropriate.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the dependency on tauri-driver and the default port, which adds useful context. However, it lacks critical details such as whether this operation is idempotent, what happens if the app is already running, error conditions, or the expected output format, leaving significant gaps for a tool that likely involves system-level interactions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise and front-loaded, consisting of only two sentences that directly convey the core functionality and a key prerequisite. Every sentence earns its place by providing essential information without redundancy or unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of launching an application (involving system dependencies and potential side-effects), no annotations, no output schema, and 100% schema coverage, the description is insufficient. It fails to explain what the tool returns, error handling, or behavioral nuances like whether it waits for the app to be ready, making it incomplete for safe and effective use by an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, so the schema already documents all three parameters (appPath, args, env) adequately. The description doesn't add any additional meaning or examples beyond what the schema provides, such as typical values for appPath or common use cases for args and env, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Launch') and target ('a Tauri application via tauri-driver'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'close_app' or 'get_app_state', which would require mentioning this is specifically for starting applications rather than managing or querying them.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some context by mentioning that 'tauri-driver must be running on the configured port (default: 4444)', which implies a prerequisite for usage. However, it doesn't offer explicit guidance on when to use this tool versus alternatives like 'close_app' or 'execute_tauri_command', nor does it specify scenarios where it should or shouldn't be used.
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 carries the full burden of behavioral disclosure. It mentions waiting for appearance and handling async UI states, but doesn't specify what happens on timeout (e.g., throws error, returns null), whether it polls continuously or uses event listeners, or any performance implications. This leaves significant behavioral gaps for an agent to understand how to use it effectively.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with two short sentences that are front-loaded and waste no words. Every part earns its place by stating the core purpose and a key usage context without redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a DOM waiting tool with no annotations and no output schema, the description is incomplete. It doesn't explain return values (e.g., returns element, boolean, or throws), error conditions, or detailed behavioral traits like polling frequency. For a tool that interacts with async UI states, more context is needed for reliable agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with clear documentation for both parameters (selector and timeout). The description adds no additional parameter semantics beyond what's in the schema, such as selector syntax examples or timeout behavior details. With high schema coverage, the baseline score of 3 is appropriate as the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('wait for an element to appear') and the target ('in the DOM'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'get_element_text' or 'click_element' which also involve DOM elements, though the 'wait for appearance' aspect provides some implicit distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides implied usage guidance with 'useful for handling async UI states,' suggesting when this tool might be appropriate. However, it doesn't explicitly state when to use this versus alternatives like 'get_element_text' (which might also wait implicitly) or provide clear exclusions or prerequisites for usage.
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 carries the full burden of behavioral disclosure. It states the tool retrieves information ('Get'), implying it's a read-only operation, but doesn't specify whether it requires authentication, has rate limits, or what happens on errors. For a tool with zero annotation coverage, this leaves significant behavioral gaps unaddressed, though it at least indicates the type of operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core purpose ('Get the current state of the application') and adds specifics without unnecessary elaboration. Every part earns its place by clarifying what information is included. It could be slightly more structured but remains highly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (0 parameters, no output schema, no annotations), the description is adequate but minimal. It covers the purpose and scope of information retrieved, but lacks details on behavioral aspects like error handling or return format. For a read-only tool with no structured output, more context on what the state includes would be helpful, though it meets minimum viability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters, and schema description coverage is 100%, so there are no parameters to document. The description appropriately doesn't discuss parameters, which is correct for this case. Baseline for 0 parameters is 4, as there's no need to compensate for missing parameter information.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with specific verbs ('Get') and resources ('current state of the application'), and lists what information is included ('whether it's running, session info, and page details'). It distinguishes from siblings by focusing on application state retrieval rather than interaction or control operations. However, it doesn't explicitly differentiate from all possible siblings in a structured way.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context through the information it retrieves (application state, session info, page details), suggesting it should be used when checking application status or context. However, it provides no explicit guidance on when to use this tool versus alternatives, nor does it mention prerequisites or exclusions. The context is implied but not clearly articulated.
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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the return behavior (base64-encoded PNG image data by default) and implies a capture action. However, it doesn't mention potential side effects like whether this pauses the application, requires specific permissions, or has any rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise with two sentences that each earn their place. The first sentence states the core purpose, and the second sentence provides crucial behavioral information about the return format. There's zero wasted verbiage.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 2 parameters, 100% schema coverage, and no output schema, the description provides good context about what the tool does and its return behavior. However, as a potentially system-interactive tool with no annotations, it could benefit from mentioning any permissions needed or system requirements.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema. The baseline score of 3 is appropriate when the schema does all the parameter documentation work.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('capture a screenshot') and target resource ('application window'), distinguishing it from sibling tools like click_element or type_text. It's not a tautology of the name and provides concrete information about what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (when you need a screenshot of the application) but doesn't explicitly state when to use this tool versus alternatives or mention any prerequisites. No guidance is provided about when not to use it or what alternatives might exist for similar functionality.
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?
With no annotations provided, the description carries full burden and does well by specifying 'gracefully' - indicating proper shutdown procedures rather than force termination. However, it doesn't disclose potential side effects, confirmation requirements, or what 'gracefully' entails operationally.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with zero waste - every word contributes essential information. Front-loaded with the core action, followed by target specification and important behavioral qualifier.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a destructive operation with no annotations and no output schema, the description is minimal but functional. It identifies the action and target but lacks details about success/failure states, side effects, or what 'gracefully' means in practice given the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has 0 parameters with 100% schema description coverage, so the baseline is 4. The description appropriately doesn't discuss parameters since none exist, focusing instead on the action's behavioral characteristics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the specific action ('close') and target resource ('currently running Tauri application'), with the adverb 'gracefully' adding important behavioral context. It distinguishes itself from sibling tools like 'launch_app' by performing the opposite operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context ('currently running') but doesn't explicitly state when to use this tool versus alternatives or prerequisites. No guidance is provided about what happens if no app is running or whether this should be used instead of force-quitting methods.
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
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/Radek44/mcp-tauri-automation'
If you have feedback or need assistance with the MCP directory API, please join our Discord server