Skip to main content
Glama
wolbarg

Wolbarg Coordination for Cursor

by wolbarg

Server Quality Checklist

50%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.2.0

  • Disambiguation1/5

    All four tools effectively serve the same purpose: reporting that Wolbarg is not initialized. They overlap completely, making it impossible for an agent to distinguish meaningful differences.

    Naming Consistency1/5

    Tool names follow no consistent pattern: mixed lowercase with underscores (wolbarg_init_required, coordination_status), compound words (workspace_briefing), and verb-object (claim_scope). No uniform style or structure.

    Tool Count1/5

    Four tools are excessive for a single, trivial function (indicating uninitialized state). One or two tools would suffice; this count wastes surface area and confuses agents.

    Completeness1/5

    The tool surface covers only the uninitialized state and provides no actual coordination functionality. If Wolbarg is supposed to enable coordination, there are no tools for any meaningful operations, making it severely incomplete.

  • Average 2.5/5 across 4 of 4 tools scored. Lowest: 1.1/5.

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

    • No community issues in the last 6 months
    • 1 commit 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

  • Behavior1/5

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

    No annotations exist, and the description only mentions a precondition and error. Behavioral traits like whether the tool is destructive, requires auth, or has side effects are not disclosed.

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

    Conciseness2/5

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

    The description is extremely short but does not earn its place—it omits essential information. Front-loading a constraint is positive, but the brevity is under-specification, not useful conciseness.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness1/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    With 6 parameters, no output schema, and no annotations, the description is wholly inadequate. It provides no actionable insight for correct invocation.

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

    Parameters1/5

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

    Schema description coverage is 0%, and the description adds no information about the six parameters (e.g., actor_id, scopes, mode). Their meanings and usage are completely unexplained.

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

    Purpose1/5

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

    The description does not state the tool's actual function; it only says it is 'Unavailable until wolbarg init' and returns an error. No verb or resource is mentioned, leaving the purpose entirely unclear.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines1/5

    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. The sibling tools (wolbarg_init_required, workspace_briefing, coordination_status) are not differentiated.

    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 exist. The description only discloses the error condition; it fails to explain normal behavior, parameters, or 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.

    Conciseness3/5

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

    The description is short and front-loaded, but it sacrifices necessary information for brevity. It earns its place but is incomplete.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness1/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    Given low complexity and no output schema, the description is drastically incomplete; it does not convey the tool's purpose, usage, or behavior beyond unavailability.

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

    Parameters1/5

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

    The schema has one parameter 'query' with 0% description coverage. The description adds no meaning beyond the schema.

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

    Purpose1/5

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

    The description only states unavailability and an error return, not what the tool does when available. The name suggests a briefing function, but the description is misleading and vague.

    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?

    It implies a precondition (wolbarg init) but offers no guidance on when to use this tool versus siblings like 'wolbarg_init_required' or alternatives.

    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, the description carries the burden of behavioral disclosure. It only states the output (reports not initialized) but does not mention whether the operation is read-only, requires permissions, has side effects, or how it handles errors. This is insufficient 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.

    Conciseness4/5

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

    The description is extremely concise with one short sentence. It wastes no words. However, it lacks structure (e.g., front-loading key info) and could be slightly more informative without losing conciseness. Still, it earns a high score for brevity.

    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 no parameters and no output schema, the description is the sole source of information. It covers the basic purpose but omits details such as the return format, when it is called, or how it interacts with sibling tools. For a simple status tool, this is minimally adequate but not complete.

    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 no parameters, so the description need not add parameter meaning. Schema coverage is trivially 100%. The baseline score of 4 is appropriate as there is no need for additional parameter semantics.

    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's action: reporting that Wolbarg is not initialized for the workspace root. It uses a specific verb (reports) and resource (initialization status), making its purpose clear. However, it may be too narrow by implying it always reports 'not initialized' rather than the general status.

    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 like 'wolbarg_init_required' or 'workspace_briefing'. It does not mention prerequisites, context, or exclusions, leaving the agent without direction for appropriate invocation.

    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?

    The description discloses that the tool returns instructions for initialization, which is appropriate for a non-destructive info tool. However, without annotations, it could provide more detail about what the setup instructions entail or any 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 a single, very concise sentence that conveys all necessary information without any unnecessary words. It is efficiently structured for quick parsing.

    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 tool's simplicity and lack of parameters/output schema, the description is sufficient for an agent to understand its purpose and action required. However, it could benefit from briefly mentioning what the output looks like (e.g., 'returns text instructions').

    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 tool has zero parameters, and the schema coverage is 100% trivially. The description does not need to add parameter details, but it does not provide extra context about the input schema (which is empty). A score of 4 reflects that it adequately handles the lack of parameters.

    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: to provide setup instructions for Wolbarg initialization. It uses a specific verb ('call this tool for setup instructions') and distinguishes itself from sibling tools which deal with other functionalities like briefing or claiming scope.

    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?

    It explicitly instructs the user to call the tool for setup instructions, then run a specific command (npx wolbarg init) and reload MCP. This provides clear sequential usage, though it does not explicitly state when not to use it or alternatives.

    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

cursor MCP server

Copy to your README.md:

Score Badge

cursor 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/wolbarg/cursor'

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