Skip to main content
Glama

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    With only one tool, there is no possibility of confusion or overlap between tools. The single tool 'run_locust' has a clear and distinct purpose that cannot be mistaken for any other tool in this set.

    Naming Consistency5/5

    The single tool name 'run_locust' follows a clear verb_noun pattern, and with only one tool, there is perfect consistency. There are no other tools to compare against, so no inconsistencies can exist.

    Tool Count2/5

    A single tool is too few for most server purposes, as it severely limits functionality and flexibility. For a Locust server, one might expect additional tools for tasks like configuring tests, viewing results, or managing load scenarios, making this set feel incomplete and under-scoped.

    Completeness1/5

    The tool set is severely incomplete for a Locust server, which typically involves multiple aspects of load testing such as setup, execution, monitoring, and analysis. With only a 'run' tool, there are significant gaps that will cause agent failures, as it lacks coverage for configuration management, result retrieval, or test lifecycle operations.

  • Average 2.4/5 across 1 of 1 tools scored.

    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
    • 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.

  • This server has been verified by its author.

  • 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 mentions 'run' but doesn't clarify if this is a read-only operation, if it modifies state (e.g., starts a process), potential side effects (e.g., consuming resources), or expected outputs (e.g., test results). This leaves significant gaps in understanding the tool's behavior.

    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?

    The description is a single, straightforward sentence that is front-loaded and wastes no words. However, it's overly concise to the point of under-specification, which slightly reduces its effectiveness. Still, it's structurally sound with no redundant information.

    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 the complexity (6 parameters, no annotations, no output schema), the description is incomplete. It doesn't cover what the tool does beyond a high-level action, leaving the agent unsure about execution details, results, or error handling. This inadequacy is notable for a tool with multiple configuration options.

    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 description coverage is 0%, so the description must compensate but fails to do so. It doesn't explain any parameters beyond implying a 'configuration' exists. For example, it doesn't clarify what 'test_file' should contain, the meaning of 'users' or 'spawn_rate', or how 'runtime' is formatted. This leaves all 6 parameters poorly understood.

    Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

    Purpose3/5

    Does the description clearly state what the tool does and how it differs from similar tools?

    The description 'Run Locust with the given configuration' states the action ('Run') and target ('Locust'), but it's vague about what Locust is (a load testing tool) and what 'run' entails (e.g., executing tests). It doesn't distinguish from siblings, but since there are none, this is less critical. However, the purpose remains somewhat ambiguous without context.

    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, such as for performance testing scenarios, prerequisites (e.g., having Locust installed), or alternatives. With no sibling tools, differentiation isn't needed, but it still lacks any usage context, leaving the agent to infer from the tool name and parameters alone.

    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

locust-mcp-server MCP server

Copy to your README.md:

Score Badge

locust-mcp-server MCP server

Copy to your README.md:

Latest Blog Posts

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/QAInsights/locust-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server