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kodlbegiko

Bruno MCP Server

by kodlbegiko

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct purpose: listing files, getting details, and executing requests. There is no overlap in functionality.

    Naming Consistency5/5

    All tool names follow the same verb_bruno_request pattern, making the naming predictable and consistent.

    Tool Count5/5

    Three tools is a well-scoped, focused set for a Bruno request server. Each tool earns its place.

    Completeness4/5

    The server covers the core workflow of listing, inspecting, and running requests. Missing mutation operations (create/update/delete) are a minor gap but not critical for the server's apparent purpose.

  • 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
    • 15 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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    {
      "$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?

    With no annotations provided, the description is the sole source of behavioral information. It states the tool gets details and raw content but does not disclose whether it is read-only, what errors may occur (e.g., request not found), the structure of the returned data, or any side effects. This is a significant transparency gap for an agent.

    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 conveys the core function without redundancy. It is efficiently structured and front-loaded with the verb and resource.

    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?

    The tool is relatively simple with two parameters and no output schema, but the description is too sparse to be complete. It does not explain what 'structured details' includes, the format of 'raw content', or any prerequisites. The lack of an output schema increases the need for description to clarify return value semantics, which it fails to do.

    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?

    The input schema covers 100% of the parameters, with descriptions for both 'request_name' and 'project_path', including an example for request_name. The tool description adds no additional parameter information, so the baseline of 3 is appropriate; the schema already provides sufficient semantics.

    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 identifies the action (get), the resource (specific Bruno request file), and the type of output (structured details and raw content). This distinguishes it from sibling tools like list_bruno_requests (listing all) and run_bruno_request (executing), making its purpose 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?

    The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention that this is for a single request while list_bruno_requests is for listing, or that run_bruno_request executes rather than retrieves details. Sibling names provide context, but the description itself offers no usage directives.

    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 must fully disclose behavioral traits. It indicates a read-only listing operation but does not mention behaviors like recursive search, file ordering, or output format. This leaves the agent uncertain about what exactly will be returned.

    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 remarkably concise, consisting of two short sentences. It front-loads the core purpose and adds the optional parameter in a natural way, with no wasted words.

    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?

    The tool is simple (one optional param, no output schema), but the description fails to specify what information is returned (e.g., filenames, full paths, metadata) or whether the listing is recursive. Given the lack of an output schema, this is a meaningful gap for an agent.

    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?

    The input schema already provides a full description for the only parameter (project_path) with 100% coverage. The tool description adds the context 'collection root' but does not go beyond the schema in explaining the parameter's meaning or behavior.

    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 function with a specific verb and resource: 'List all Bruno request files in the collection root.' It is distinct from sibling tools 'get_bruno_request_detail' and 'run_bruno_request', which focus on viewing details and executing requests respectively.

    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 gives clear context that this tool lists files at the collection root and mentions the optional project_path parameter. However, it does not explicitly explain when to use this tool over the siblings, such as saying 'use this to browse available requests before running them.'

    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 carries the full burden. It mentions 'using the local Bruno CLI' and 'get status and outputs,' but does not disclose potential side effects, prerequisites (e.g., project_path), or the format of outputs. This is insufficient for an execution tool.

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

    Conciseness5/5

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

    The description is a single concise sentence that front-loads the action and outcome. It contains no filler or repetition.

    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?

    With no output schema and no annotations, the description should clarify expected outputs and execution context. It vaguely says 'get status and outputs' but does not explain the structure or behavior for optional parameters, making it incomplete for a tool with moderate complexity.

    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?

    The input schema has 100% coverage with descriptions for all parameters, so the baseline is 3. The tool description adds no parameter-specific semantics beyond what the schema already provides.

    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 uses a specific verb ('Execute') and resource ('Bruno API request'), clarifies it uses the local CLI, and mentions status/output. This clearly distinguishes it from siblings that list requests or get request details.

    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 does not explicitly state when to use this tool versus alternatives. However, the tool name and sibling names imply that this is for executing a request, while siblings are for listing/detailing, so usage is implied but not stated.

    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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  • Evaluate tool definition quality.

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