Skip to main content
Glama
OpenSourceWTF

local-vibes

by OpenSourceWTF
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Local

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.0

  • Disambiguation5/5

    Only one tool exists, so there is no ambiguity or overlap between tools. The tool's purpose is clear and distinct by default.

    Naming Consistency5/5

    With a single tool named 'delegate', there is no pattern to contradict. The name is a simple, clear verb that aligns with its action.

    Tool Count3/5

    The server has only one tool, which feels thin and borderline. However, the tool is broad enough to cover a variety of delegation tasks, making it somewhat self-sufficient despite the low count.

    Completeness4/5

    The delegate tool covers the core workflow of delegating tasks and receiving results, which is sufficient for the stated purpose. Minor gaps exist around task management (e.g., status, cancellation), but the synchronous design makes these less critical.

  • Average 4.7/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 14 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

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

    If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.

    MCP servers without a LICENSE cannot be installed.

  • 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

  • Behavior5/5

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

    With no annotations, the description fully discloses key behaviors: reads/edits files, runs shell commands confined to working_dir, returns a summary plus git change report, and is safe for concurrent invocation with in-flight runs bounded by LOCAL_VIBES_MAX_CONCURRENCY. This goes well beyond minimal expectations.

    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?

    About five sentences, each carrying distinct value: purpose, use cases, sandbox behavior, task composition advice, and concurrency notes. It is front-loaded with the main action and uses a dash-separated list for examples. Slightly longer than minimal, but all content is pertinent.

    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?

    Covers purpose, usage, behavioral constraints, output format, and concurrency. No output schema exists, but the description mentions the return format (summary plus git change report). It lacks explicit failure-mode or error-handling details, but given the tool complexity and lack of annotations/siblings, it is substantially 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?

    Schema coverage is 100%, so each parameter already has a description. The tool description adds extra context by clarifying that the task must be self-contained, working_dir is the sandbox root, and read_only disables writes/edits/bash. This enriches the schema without redundancy.

    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 opens with a specific verb and resource: 'Delegate a self-contained coding or research task to a LOCAL model running in its own sandboxed agent loop.' It clearly defines what the tool does and distinguishes it from inline execution. Even without sibling tools, the purpose is unmistakable.

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

    Usage Guidelines5/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    Explicit guidance is given with 'USE PROACTIVELY to offload grunt work' followed by concrete examples (codebase searches, boilerplate, mechanical multi-file edits, test scaffolding). It also advises giving 'ONE clear, self-contained task with enough context to act without follow-up questions' and notes concurrent safety and a concurrency bound.

    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

local-vibes MCP server

Copy to your README.md:

Score Badge

local-vibes 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/OpenSourceWTF/local-vibes'

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