Augments MCP Server

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Server Quality Checklist

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Latest release: v7.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: comparison, error diagnosis, server health, API details, migration guides, version info, dependency scanning, and API search. No overlapping functionality.
Naming Consistency4/5
Most tools use a consistent verb_noun pattern (compare_packages, diagnose_error, get_api_context, get_migration_guide, get_version_info, scan_project_deps, search_apis). 'diagnostics' is a noun-only outlier, slightly breaking consistency.
Tool Count5/5
Eight tools is well-scoped for the domain of npm package analysis and development assistance. Each tool covers a key area without redundancy.
Completeness5/5
The tool surface covers all major development needs: package comparison, error diagnosis, API exploration, version management, migration planning, project auditing, and concept search. No obvious gaps.
Average 3.8/5 across 8 of 8 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on March 13, 2026
- 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.
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```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
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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 full burden. It states the tool reads package.json, but does not disclose whether it modifies files, error handling (e.g., file not found), rate limits, or output behavior. The description is too minimal to inform the agent of operational traits beyond the obvious read-only scan.
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 two sentences with no wasted words. It front-loads the primary purpose and immediately mentions the input file. Every sentence is essential and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description should explain what the tool returns (e.g., list of issues, formatted report) or any side effects. It does not. For a scanning tool with two parameters, the agent is left guessing the output structure and failure modes. This is a significant gap.
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% with both parameters documented. The description adds value by linking the check types ('updates', 'deprecated', 'security') to their meanings (outdated packages, major updates, deprecated packages, security advisories). However, it does not provide additional syntax, format, or dependency context beyond what the schema already offers.
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 scans project dependencies for outdated packages, major updates, deprecated packages, and security advisories. It specifies it reads package.json. However, it does not explicitly differentiate from sibling tools like compare_packages or get_version_info, which could be confused for similar purposes.
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 provides no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, typical use cases, or when to avoid using it. The usage context is only implied by the action description.
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, the description carries full burden. It states the operation is non-destructive and lists return contents, but does not disclose potential behaviors such as error handling for invalid versions, data freshness, or whether external API calls are made. This provides moderate transparency.
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 a single focused sentence that immediately states the action and what is returned. No unnecessary words, and the structure supports quick comprehension.
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 simple retrieval tool with three well-described parameters and no output schema, the description covers the essential functionality and return types. Minor gaps exist (e.g., no mention of version format validation), but overall it is sufficiently complete for the agent to understand and invoke the tool correctly.
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%, so the baseline is 3. The description does not add any semantic meaning beyond the schema descriptions; it merely restates the overall purpose. No parameter-specific guidance is offered.
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 retrieves a migration guide between package versions, listing specific returned elements (breaking changes, new features, deprecations, etc.). This distinguishes it from sibling tools like 'compare_packages' which compares packages rather than versions within a package.
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?
No guidance is provided on when to use this tool versus alternatives. There is no mention of prerequisites, limitations, or typical use cases, leaving the agent to infer usage from the name and description alone.
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?
No annotations are provided, so the description carries the full burden. It discloses that the tool accesses changelogs for breaking changes and new features, indicating a read-only behavior. However, it does not describe error handling, rate limits, or what happens if a package is not found.
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 two sentences, each serving a purpose: the first defines core functionality, the second highlights recent enhancements. No unnecessary information.
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 the lack of output schema, the description provides a good overview of what the tool returns: version info, available versions, breaking changes, and features from changelogs. It could be more specific about the output format, but it is largely sufficient.
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%, but the description adds value by explaining that the tool provides 'breaking change detection' and 'available versions', which clarifies the purpose of the fromVersion and toVersion parameters. This goes beyond the schema's basic definitions.
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 it gets version info, available versions, and breaking change detection for npm packages, with specific verb and resource. It also mentions included features from changelogs, which distinguishes it from sibling tools like compare_packages or get_migration_guide.
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 provides no explicit guidance on when to use this tool versus alternatives, such as compare_packages for comparing packages or get_migration_guide for migration steps. Context signals indicate sibling tools but no usage rules are given.
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, description fully bears burden: it states it matches, searches, and finds documentation, implying a read-only, aggregating behavior. No contradictions; could mention response format but sufficient.
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, front-loaded with verb and resource, no wasted words—every sentence adds value.
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?
No output schema; description doesn't specify return format (e.g., list of links or text), leaving some ambiguity. Adequate but not fully complete.
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 covers all 3 parameters with descriptions; tool description adds no extra meaning beyond what schema already provides, so 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?
Description clearly states verb 'diagnose' and resource 'error message or stack trace', and lists specific actions (matching patterns, searching issues, finding docs), distinguishing it from siblings like search_apis or get_migration_guide.
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 (when you have an error), but no explicit guidance on when not to use or comparison with alternative tools like search_apis.
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, the description carries the burden of behavioral disclosure. It lists the data categories returned but does not mention response format, potential side effects (none expected), or any access requirements. This is adequate for a simple read-only tool but lacks depth.
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 a single sentence that front-loads the main purpose ('Get server health information') and lists specific items efficiently. Every word serves a purpose with no redundancy.
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 no output schema, the description partially compensates by enumerating returned data fields. However, it omits details on response structure (e.g., JSON object) and does not address missing annotation information. For a simple health tool, it is largely complete but could be more explicit.
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?
There are zero parameters, and the schema coverage is 100%. Per guidelines, the baseline is 4. The description does not need to add parameter-specific meaning, and it does not detract.
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 verb 'Get' and the resource 'server health information', and lists specific items (version, uptime, memory, cache, Node.js version). This distinguishes it from sibling tools like 'diagnose_error' (focused on errors) and 'get_version_info' (version-only).
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 implies usage for general health monitoring but does not explicitly state when to use this tool versus alternatives like 'diagnose_error' or 'get_version_info'. No when-not or exclusion criteria are provided.
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?
No annotations are provided, so the description carries the full burden. It states that the tool returns API signatures, parameters, etc., but does not explicitly declare it as read-only or mention any side effects, rate limits, or prerequisites. The name implies it is a lookup, but explicit transparency would improve the score.
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 two sentences long: the first states the core purpose, and the second gives examples and a usage recommendation. It is front-loaded, concise, and avoids unnecessary detail.
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?
The description covers the tool's inputs (natural language query, optional filters) and outputs (signatures, params, docs, examples). However, it does not specify the output format or structure (since no output schema), nor does it mention constraints like network requirements or limits. For a 5-parameter tool, this is mostly complete but missing a few details.
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%, and the input schema already provides clear descriptions for all parameters. The description adds only a brief mention of natural language handling, which relates to the 'query' parameter, but does not provide additional semantic value beyond what the schema already includes.
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 it gets 'precise API signatures, parameters, return types, prose documentation, and code examples for any npm package.' The verb 'Get' and specific resource are well-defined, and the scope (npm packages) distinguishes it from siblings like 'diagnose_error' or 'scan_project_deps'.
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 recommends this tool ('RECOMMENDED: ... Always try this first.'), implying it is the default for API queries. It provides example queries, which clarifies the kind of input to use. However, it does not list alternative sibling tools or specify when not to use this tool.
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 must disclose behavioral traits. It does not mention that the tool is read-only, nor any related side effects, rate limits, or output details. The only behavioral insight is support for concept search, which is more of a feature than a transparency about side effects.
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 extremely concise with two sentences, no redundancy, and begins with the core purpose. Every word adds value, and the structure efficiently communicates the tool's utility.
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 the schema covers all parameters and no output schema is present, the description adequately explains the search functionality and concept matching. It lacks details on how matches are ranked or how framework limiting works, but overall it provides sufficient context for an AI agent to decide when to invoke this 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 coverage is 100% with descriptions for all parameters. The description adds significant value for the 'query' parameter by providing concrete examples (e.g., 'state management' matching useState, createStore), enhancing understanding beyond the schema. For 'frameworks' and 'limit', the schema already provides adequate descriptions, so the description adds minimal extra meaning.
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: searching for APIs by concept when exact name is unknown. It provides examples like 'state management' matching multiple APIs, which effectively communicates the tool's function and distinguishes it from siblings that likely handle exact lookups or dependency scanning.
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 advises use when 'you don't know the exact name' and supports concept search, providing clear context. However, it does not explicitly state when not to use this tool or mention alternatives like get_api_context for exact lookups, slightly reducing clarity.
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?
No annotations are provided, so the description must carry the burden. It lists what is compared but does not disclose data sources, network dependencies, rate limits, or whether results are real-time. This is adequate but not thorough.
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 concise sentences—first describing functionality, second suggesting use case. No redundant information; every word is purposeful.
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 low complexity (2 parameters, no nested objects) and no output schema, the description covers purpose and usage adequately. However, it omits details about result format or potential limitations, leaving some gaps.
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?
The schema covers both parameters with descriptions (100% coverage). The description adds value by enumerating comparison dimensions (e.g., 'downloads, bundle size') that are not in the schema, providing richer context beyond parameter names.
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 it compares npm packages side-by-side, listing specific aspects like downloads and bundle size. It distinguishes itself from sibling tools (e.g., diagnose_error, scan_project_deps) by focusing on comparison for alternatives.
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 provides clear guidance: 'Great for choosing between alternatives.' It implies when to use but lacks explicit when-not-to-use or direct references to alternative tools.
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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