MCP Compass
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly defined as recommending MCP servers based on descriptions, and no other tools exist to cause confusion.
Naming Consistency5/5A single tool inherently exhibits perfect naming consistency, as there are no other tools to compare against. The tool name 'recommend-mcp-servers' follows a clear verb-noun pattern and uses hyphens consistently.
Tool Count2/5One tool is too few for a server named 'MCP Compass', which suggests a broader scope of functionality for exploring or navigating MCP servers. A single recommendation tool feels thin and incomplete for this apparent purpose, lacking supporting tools like search, filter, or get details.
Completeness2/5The tool surface is severely incomplete for the inferred domain of MCP server exploration. While the tool can recommend servers, there are significant gaps: no ability to search, filter, get detailed information, list categories, or manage preferences. This will likely cause agent failures when trying to perform comprehensive MCP server discovery tasks.
Average 3.4/5 across 1 of 1 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 2 issues responded to in the last 6 months
- No commit activity data available
- 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 explores the internet and returns a list with IDs, descriptions, GitHub URLs, and similarity scores, which covers some behavioral aspects. However, it lacks details on rate limits, authentication needs, potential errors, or how the exploration works (e.g., API calls, web scraping). For a tool with no annotation coverage, this leaves significant gaps.
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 appropriately sized and front-loaded, starting with the usage context and then detailing the action and return values. It uses three sentences efficiently, with no wasted words, though it could be slightly more polished (e.g., 'findn' typo).
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 moderate complexity (1 parameter, no output schema, no annotations), the description is somewhat complete but has gaps. It explains the purpose, usage, and return format, but lacks behavioral details like error handling or exploration mechanics. Without annotations or an output schema, more context would be beneficial 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?
The schema description coverage is 100%, providing detailed examples and requirements for the 'query' parameter. The description adds minimal value beyond this, only mentioning that it's 'based on the description of the MCP Server needed.' Since the schema does the heavy lifting, the baseline score of 3 is appropriate.
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: 'explores and recommends existing MCP servers from the internet, based on the description of the MCP Server needed.' It specifies the verb (explores/recommends) and resource (MCP servers), though it doesn't need to differentiate from siblings since none exist. The purpose is specific but could be slightly more precise about the exploration mechanism.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: 'when there is a need to find external MCP tools.' It explicitly ties usage to the query parameter's description of the needed MCP server. However, it doesn't mention when not to use it or alternatives, which isn't critical here since no siblings exist.
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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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.
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