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BrainDAO

NEAR MCP Server

by BrainDAO
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TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.1.2

  • Disambiguation5/5

    Each tool has a clear, distinct purpose: listing, stopping, or starting event watches. No overlap or ambiguity.

    Naming Consistency4/5

    All tools use a verb_near_event pattern (list_watched, stop_watching, watch). Minor inconsistency in tense (watched vs watching) but overall predictable.

    Tool Count4/5

    3 tools is appropriate for a focused event-watching server. Not over- or under-scoped.

    Completeness4/5

    Covers the basic lifecycle: create (watch), read (list), delete (stop). Missing update but that is often unnecessary for event filters.

  • 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
    • 0 commits in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is failing

  • This repository is licensed under ISC License.

  • This repository includes a README.md file.

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    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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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 must carry the full burden. It only states the action without describing side effects, idempotency, or prerequisites (e.g., whether a watch must exist).

    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 sentence, front-loading the core purpose. While brief, it avoids unnecessary words and is efficiently structured.

    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?

    For a simple tool with two required parameters and no output schema, the description is adequate. However, it could mention the expected result or behavior when no watch exists.

    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?

    Schema description coverage is 100% for both parameters. The description adds no additional meaning beyond the schema's parameter descriptions, so the baseline score of 3 is appropriate.

    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 'Stop watching for specific events on a NEAR contract' clearly states the tool's purpose with a specific verb and resource. However, it does not differentiate from the sibling tool 'watch_near_event' beyond the opposite action, which could be clearer.

    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?

    No guidance on when to use this tool versus alternatives like 'watch_near_event' or 'list_watched_near_events'. The description implies use for stopping a watch but lacks explicit context or prerequisites.

    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 provided, so the description must disclose behavioral traits. It mentions 'process them with AI responses' but does not explain how responses are generated, polling behavior, or persistence. Lacks details on side effects or requirements.

    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?

    Single sentence that is clear and front-loaded. Could be slightly more structured, but efficiently conveys the core action.

    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 5 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the polling mechanism, lifecycle (e.g., how to stop), or what 'process with AI responses' entails. Sibling tools hint at a monitor/stop pattern.

    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?

    Schema description coverage is 100%, so the schema already documents each parameter. The description does not add significant meaning beyond what is in the schema. Baseline 3 is appropriate.

    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?

    Clearly states the verb 'start watching' and the resource 'events on a NEAR contract', and adds the purpose 'process them with AI responses'. Differentiates from siblings by specifying the start action, but could be more explicit about the lifecycle.

    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?

    No guidance on when to use this tool vs siblings (list_watched_near_events, stop_watching_near_event). Does not provide context about prerequisites or when not to use.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

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

    No annotations provided, so description carries full burden. It correctly identifies as a read operation without side effects. However, it could mention output details like the structure of returned data or whether pagination applies.

    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?

    Single, concise sentence with no wasted words. Front-loaded with the core action and resource.

    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 (1 optional param, no output schema), the description is mostly complete. It could be improved by hinting at the return value format (e.g., list of events with fields).

    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?

    Schema coverage is 100% with one parameter 'includeStats' documented. The description does not add extra meaning beyond the schema, meeting the baseline for full coverage.

    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 action (list), the resource (currently watched NEAR events), and the included information (status). It distinctly separates from sibling tools stop_watching_near_event and watch_near_event.

    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 implies usage for viewing watched events but does not provide explicit when-to-use or when-not-to-use guidance compared to siblings. It lacks context on prerequisites or alternatives.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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