MCP Opener
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: open_browser for URLs, open_file for files, and open_folder for directories. There is no overlap in functionality, making it easy for an agent to select the correct tool based on the target type.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern (open_browser, open_file, open_folder) with the same verb 'open' and descriptive nouns. This uniformity enhances readability and predictability.
Tool Count5/5With 3 tools, the server is well-scoped for its purpose of opening resources (URLs, files, folders). Each tool earns its place by covering a distinct aspect of the domain without redundancy or bloat.
Completeness5/5The tool surface is complete for the domain of opening resources, covering URLs, files, and folders. There are no obvious gaps, as these three categories encompass the typical use cases for an opener utility.
Average 3.4/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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 opens a file with its default application, implying a system-level action that may launch external apps, but doesn't mention potential side effects like requiring specific permissions, handling errors, or system dependencies. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it easy to understand quickly. Every part of the sentence contributes to clarity, with no wasted information.
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 (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the basic action but lacks details on behavioral aspects like error handling or system requirements. Without annotations or output schema, it should provide more context for safe use, but it meets the bare minimum for a simple tool.
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 single parameter 'path' documented in the schema as 'Absolute or relative path to the file to open'. The description adds no additional meaning beyond this, such as examples or constraints. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.
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 ('Open') and resource ('a file'), specifying it opens with the default application. It distinguishes from sibling tools like 'open_browser' and 'open_folder' by focusing specifically on files, though it doesn't explicitly contrast them. The purpose is unambiguous but could be more specific about sibling differentiation.
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 like 'open_browser' or 'open_folder'. It lacks context about scenarios where opening a file is appropriate compared to opening a browser or folder, and offers no prerequisites or exclusions. Usage is implied by the action but not explicitly defined.
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 action ('Open a folder') but does not describe what happens upon execution (e.g., whether it launches an application, requires user permissions, handles errors, or has side effects). This leaves significant gaps in understanding the tool's behavior beyond the basic action.
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 front-loads the core action and resource, with no wasted words. It is appropriately sized for the tool's simplicity, making it easy to parse and understand quickly.
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 (one parameter, no output schema, no annotations), the description is minimally adequate. It covers the purpose and basic usage but lacks details on behavioral traits, error handling, or integration with the system, which could be helpful for an agent to invoke it correctly in varied contexts.
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 the 'path' parameter fully documented. The description does not add any meaning beyond what the schema provides (e.g., no examples of path formats or constraints), so it meets the baseline of 3 for high schema coverage without compensating with extra details.
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 ('Open a folder') and resource ('in the system file manager'), with explicit examples (Nautilus, Finder, Explorer) that distinguish it from sibling tools like open_browser and open_file. It provides a complete, unambiguous purpose statement.
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 by specifying the tool opens folders in file managers, but it does not explicitly state when to use this tool versus alternatives like open_file or open_browser. No guidance on prerequisites, exclusions, or specific contexts is provided, leaving usage somewhat open to interpretation.
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 of behavioral disclosure. It adds useful context about supported browsers and URL protocol requirements (implied by the schema), but it does not cover aspects like error handling, platform dependencies, or what happens if the browser is not installed. The description provides some behavioral insight but leaves gaps for a mutation 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 appropriately sized and front-loaded, consisting of a single, efficient sentence that directly states the tool's function and supported browsers without unnecessary details. Every part of the sentence earns its place by providing essential information, making it highly concise and well-structured.
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 complexity (simple mutation with one parameter), no annotations, and no output schema, the description is moderately complete. It covers the basic action and browser support but lacks details on behavioral traits like error responses or system requirements. For a tool with no annotations, it should do more to fully inform the agent, resulting in an adequate but incomplete description.
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%, with the parameter 'url' fully documented in the schema (including protocol requirements). The description does not add any additional meaning or semantics beyond what the schema provides, such as examples or edge cases. Given the high schema coverage, the baseline score of 3 is appropriate as the description does not compensate or enhance parameter understanding.
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 ('Open a URL') and resource ('in the preferred web browser'), distinguishing it from sibling tools like open_file and open_folder which handle different resources. It provides explicit detail about supported browsers (Firefox, Chrome, system default), making the purpose unambiguous and distinct.
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 by specifying supported browsers, but it does not explicitly state when to use this tool versus alternatives like open_file or open_folder. It provides some context (browser types) but lacks guidance on exclusions or direct comparisons with sibling tools, leaving the agent to infer appropriate usage scenarios.
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/3viky/mcp-opener'
If you have feedback or need assistance with the MCP directory API, please join our Discord server