mcp-registry-interface
Server Quality Checklist
Latest release: v1.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: searching, retrieving details, listing categories, refreshing data, and getting help. There is no overlap or ambiguity between them.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with lowercase and underscores (e.g., registry_search_servers, registry_get_server_details). 'help' is a minor deviation but is a conventional verb-like exception in many toolkits.
Tool Count5/5With exactly 5 tools, the set is well-scoped for a registry interface. Each tool covers a needed function without redundancy or bloat.
Completeness4/5The core read and maintenance operations (search, get details, list categories, refresh) are all present. A list-all servers function could be considered missing, but search likely covers that use case adequately.
Average 3.7/5 across 5 of 5 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits 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.
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glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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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?
With no annotations provided, the description carries full responsibility for behavioral disclosure. It only restates the purpose ('Get detailed information') without revealing response format, error behavior (e.g., what if serverId is not found), or any side effects. This is minimal 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.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no wasted words. It is concise and structured clearly, though it is somewhat under-specified. The efficiency is good, but it could have benefited from additional context without becoming verbose.
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?
The tool is simple (one parameter, no output schema, no annotations), yet the description still feels incomplete. It does not explain what 'detailed information' includes, whether the result is a single object, or how to handle nonexistent server IDs. Given the lack of annotations and output schema, more context is needed for an agent to use it correctly.
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% coverage: serverId is described as 'Server ID or name'. The description adds no additional meaning about the parameter, but the schema already documents it adequately. Baseline of 3 is appropriate because the description does not compensate or add extra context.
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 tool's purpose: to get detailed information for a specific MCP server. It uses a specific verb ('Get') and resource ('detailed information about a specific MCP server'), distinguishing it from sibling tools like search (registry_search_servers) and list (registry_list_categories).
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. It does not mention prerequisites (e.g., needing a known server ID) or when to prefer search_servers instead. The context from sibling names implies use after finding a server, but the description itself offers no such direction.
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 only mentions the generic search action and the source ('GitHub repositories and registries') but fails to indicate side effects, data freshness, network usage, result ordering, or any limitations. This leaves the agent without crucial context for a tool with no annotation safety hints.
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, concise sentence that immediately states the tool's purpose. No unnecessary details or filler are present, and it is appropriately front-loaded with the primary action.
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?
The tool is relatively simple, but the description omits any mention of return format or result behavior. It also does not reference the possibility of using registry_list_categories to discover valid category values. While the schema covers parameters, the lack of output schema and minimal description leaves some gaps, though it is minimally viable.
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 all three parameters (query, category, limit) described directly in the schema. The description adds no additional meaning or context for these parameters, so the baseline score of 3 applies.
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 tool's function: 'Search for MCP servers from GitHub repositories and registries.' It uses the specific verb 'search' and identifies the resource ('MCP servers') and source context, which distinguishes it from sibling tools like registry_get_server_details and registry_list_categories.
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 through the verb 'search' but provides no explicit when-to-use or when-not-to-use guidance. There is no mention of alternatives (e.g., 'for details, use registry_get_server_details') or exclusions, so it's only minimally guided.
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?
There are no annotations, so the description alone must disclose behavior. It reveals that the operation bypasses the cache, but does not explain side effects such as overwriting existing data, whether auth is required, or whether the refresh can fail. The mutating nature is hinted but not elaborated.
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?
A single, front-loaded sentence conveys the core action and a distinguishing trait (cache bypass). Every word earns its place; no repetition or filler exists.
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?
With no annotations, no output schema, and a 0-parameter design, the description is minimally sufficient, but it omits what a call returns and potential side effects. The cache-bypass detail adds value, yet the overall picture is not fully formed for a tool that mutates state.
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 zero parameters and the schema is fully defined (100% coverage) with an empty object. No parameter explanation is needed beyond what the schema already provides, so this meets the baseline.
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 action (Refresh), the target (server data), and the source (GitHub). It also distinguishes the tool from sibling tools (search, get, list) by indicating a write/update 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 mention of bypassing cache implies use when fresh data is needed, but there is no explicit guidance on when to use this tool versus the search/get/list siblings, nor any when-not-to-use conditions. Usage is only implied, not stated.
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 for behavioral context. It indicates the data source ('from GitHub data') which is useful, but does not disclose any other behavior such as whether the data is cached, live, or refreshed, or what the returned data structure looks like. This is a significant gap for a tool with no annotation support.
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, concise sentence that is front-loaded with the verb and resource. Every word earns its place, with no redundancy or filler.
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 simple, zero-parameter tool, the description is adequately complete: it states the action, the target object, and the data source. There is no output schema, but the return type (a list of categories) is strongly implied. It could be enriched with details about category format or data freshness, but given the tool's simplicity, the description is sufficient.
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 zero parameters, so the schema needs no explanation. The description doesn't need to add parameter semantics, and the baseline of 4 applies because there is nothing to clarify.
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 a specific action ('List') and resource ('server categories'), with a useful source qualifier ('from GitHub data'). It is distinct from sibling tools like registry_search_servers and registry_get_server_details, which involve searching or retrieving details rather than listing categories.
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 naming the function and its purpose, but it does not explicitly state when to choose this tool over its siblings or mention any exclusions. The context of sibling tool names gives some implied guidance, but the description itself lacks direct when-to-use wording.
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, the description carries the full burden. It clearly indicates a read-only operation ('Get comprehensive documentation') and describes the tool's behavior accurately. While it does not list side effects, they are inherently absent, and the description is sufficient for a documentation 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, concise sentence with the key information front-loaded. It avoids unnecessary words and fully communicates the tool's purpose without fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description is complete. It specifies the scope ('all registry-interface functions') and given the sibling tools, it is clear that it covers those functions. No additional context is needed.
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 zero parameters, so the description does not need to add parameter meaning. The schema is trivially complete at 100% coverage, and the baseline for 0 params is 4; the description adds no parameter details but does not need to.
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 uses a specific verb ('Get') and resource ('comprehensive documentation for all registry-interface functions'), clearly distinguishing itself from sibling tools that perform registry operations (e.g., search, get details, list, refresh).
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 clearly implies use whenever documentation is needed, and the scope ('all registry-interface functions') provides context. However, it does not explicitly state when not to use it or mention alternatives, so it lacks the explicit exclusions needed for a 5.
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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