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aidevelopers2

remoteopenclaw-mcp

by aidevelopers2
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JavaScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.2.0

  • Disambiguation5/5

    Each tool has a distinct target (MCP servers, plugins, skills), with clear descriptions that leave no ambiguity. An agent can easily differentiate them.

    Naming Consistency5/5

    All tools follow the exact same pattern: 'search_' followed by the plural noun of the target resource (servers, plugins, skills). This is perfectly consistent.

    Tool Count5/5

    Three tools is appropriate for a focused search-oriented server. Each tool covers a distinct category and is justified by the directory size mentioned.

    Completeness4/5

    The server covers the main asset types listed (servers, plugins, skills). There are no obvious gaps given its stated purpose; however, it might miss other potential resources like 'agents' or 'clients', but that's minor given the description.

  • Average 3.3/5 across 3 of 3 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 4 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.

  • 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.json to 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

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations provided, so the description carries full burden. It describes the return format (names, descriptions, links, popularity) which gives a reasonable behavioral overview. However, it does not explicitly state that the operation is read-only or discuss side effects, rate limits, or authentication.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    Single sentence that efficiently conveys the tool's action, data source, scale, target clients, and return fields. No wasted words, though it could be slightly more structured.

    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 low complexity (2 params, no output schema, no annotations), the description provides a complete picture of the tool's functionality and output. It does not explain pagination or ordering, but these are minor omissions.

    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 50%: only 'query' has a description. The tool description adds context about the directory and what is returned but does not explain the 'limit' parameter. This partially compensates for the missing schema descriptions.

    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 searches a directory of MCP servers, specifying the directory name, count, and intended clients. It does not explicitly differentiate from sibling tools 'search_plugins' and 'search_skills', but the purpose is unambiguous.

    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 on when to use this tool versus alternatives. The description only states what it does without mentioning exclusions or when not to use it.

    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 provided, so description must cover behavioral traits. It only states the skill count and return fields but omits details like pagination, rate limits, or authentication needs. Minimal behavioral context.

    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, well-structured sentence that front-loads the action and efficiently conveys key information. No extraneous text.

    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 the tool's simplicity (2 params, no output schema), the description provides essential info (source, return fields, skill count) but lacks details on pagination, ordering, or how 'limit' behaves. Adequate but not comprehensive.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    Schema describes 'query' fairly with examples, but 'limit' lacks description. Tool description adds no additional meaning to parameters compared to schema. With 50% schema coverage, description should compensate but does not.

    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 'Search', the resource 'directory of agent skills', and specifies the return values. It distinguishes from siblings by mentioning 'agent skills' and naming specific platforms.

    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 explicit guidance on when to use this tool over siblings like search_mcp_servers or search_plugins. The description implies it's for skills but does not compare or contrast usage contexts.

    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 must disclose behavioral traits. It states what the tool does and what it returns, but lacks details on authentication, rate limits, pagination, or error handling. The mention of returning 'names, descriptions, and links' provides basic transparency but is not comprehensive.

    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, concise sentence that efficiently conveys the tool's purpose and output. No extraneous information is present; it earns its length.

    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 a simple search tool with 2 parameters and no output schema, the description is minimally complete. It covers the action and return content but omits details like sorting, pagination, or differentiation from siblings. It is adequate but leaves gaps.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters2/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    The schema has 2 parameters (query required, limit optional) with only query having a description. The tool description adds no extra meaning beyond the schema—it doesn't explain limit, format, or behavior. With 50% coverage, the description should compensate but fails to do so.

    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 searches a specific directory (Remote OpenClaw) for plugins from multiple model families (Claude Code, OpenClaw, Hermes, Codex) and specifies what it returns (names, descriptions, links). It effectively distinguishes from sibling tools search_mcp_servers and search_skills by naming the directory and plugin type.

    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 its siblings (search_mcp_servers, search_skills). There is no mention of context, prerequisites, or exclusion criteria, leaving the agent to guess the appropriate scenario.

    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.

Our badge communicates server capabilities, safety, and installation instructions.

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