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adamdude828

browser-use MCP server

by adamdude828
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Python
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Server Quality Checklist

50%
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 ambiguity or confusion between tools. The tool 'add-note' has a clear and distinct purpose that cannot be misselected against other tools.

    Naming Consistency5/5

    Since there is only one tool, it inherently follows a consistent naming pattern. The tool name 'add-note' uses a verb_noun format, which is clear and predictable, and there are no other tools to cause inconsistency.

    Tool Count2/5

    A single tool is too few for a server named 'browser-use', which suggests a broader scope related to browser interactions. This minimal set feels thin and incomplete for the implied domain, limiting functionality.

    Completeness1/5

    The tool set is severely incomplete for a browser-use server. With only an 'add-note' tool, there are obvious gaps in core browser operations like navigation, clicking, or form filling, making it inadequate for typical browser automation tasks.

  • Average 1.9/5 across 1 of 1 tools scored.

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

    • No community issues in the last 6 months
    • 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

  • 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.

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  • 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

  • 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. 'Add a new note' implies a mutation operation but fails to specify permissions needed, whether the note is persistent, if there are rate limits, or what happens on success/failure. This leaves critical behavioral traits undocumented.

    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 extremely concise at three words, with no wasted language. It's front-loaded with the core action, though this brevity comes at the cost of clarity and completeness for a tool with parameters and no annotations.

    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 the tool has 2 parameters with 0% schema coverage, no annotations, no output schema, and no sibling context, the description is severely incomplete. It doesn't explain what the tool returns, how parameters are used, or behavioral aspects, failing to provide adequate context for effective use.

    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 description mentions no parameters, while the input schema has 2 required parameters (name, content) with 0% schema description coverage. This creates a complete gap in understanding what 'name' and 'content' represent, their formats, or constraints, making parameter usage ambiguous.

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

    Purpose2/5

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

    The description 'Add a new note' restates the tool name 'add-note' with minimal elaboration, making it tautological. It specifies the verb 'add' and resource 'note' but lacks any distinguishing details about scope, format, or context that would clarify what kind of note is being added or where it's stored.

    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?

    The description provides no guidance on when to use this tool, such as prerequisites, alternatives, or specific scenarios. With no sibling tools mentioned, it doesn't differentiate from other note-related operations, leaving the agent without context for appropriate invocation.

    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.

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