Skip to main content
Glama

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one posts a board, the other performs a matching check. No overlap or ambiguity between them.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern (post_board, match_board), making the naming predictable and uniform.

    Tool Count3/5

    With only two tools, the server is at the low end of acceptable scope. It's borderline but may be intentional for a narrow, focused purpose.

    Completeness3/5

    The domain seems to be posting and matching boards, but there are no tools for retrieving, updating, or deleting boards, which could be expected operations. The coverage is minimal but not severely broken for its stated purpose.

  • Average 3/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 8 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.

  • This server has been verified by its author.

  • 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?

    The description reveals that the tool is optimized for zero-token (low-cost) pre-filtering and runs at Cloudflare Edge, giving some performance/latency context not inferable from the schema. However, it does not state whether the operation is read-only, what side effects might occur, what the return type is, or how it behaves on no match. With no annotations to fill the gap, the tool's safety and state-changing profile remain ambiguous.

    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 exactly one short sentence and wastes no words. It front-loads the key concept (zero-token pre-filtering) and only adds a useful deployment context ('Cloudflare Edge'). This is an ideal level of conciseness.

    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 a 4-parameter tool with a nested object and no output schema, the description leaves too much unsaid: no return type, no failure modes, no explanation of what a 'match' means, and no relationship to the sibling tool. The description might suffice for a trivial utility, but for an AI agent deciding whether to invoke this tool and how to interpret results, it is insufficient.

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

    Parameters2/5

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

    With 0% parameter description coverage in the schema, the description needed to clarify how 'domain', 'identity', 'intent_space', and 'similarity_threshold' relate to the match operation. Although the parameter names hint at a domain/identity against an intent space, the description does not explain their roles, accepted formats, or how similarity_threshold impacts results. The one-word description does not compensate for the missing schema documentation.

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

    Purpose3/5

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

    The description provides a specific verb ('perform') and a noun phrase ('pre-filtering match check'), distinguishing it from a write operation, but it does not clarify what is being matched or what a 'match check' entails. It partially differentiates from the sibling 'post_board' by implying a read/check operation, but not explicitly. A clearer explanation of the input-output relationship would improve clarity.

    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 gives no guidance on when to use this tool versus 'post_board' or any alternative. No mention of use cases, exclusions, or preconditions such as 'use when you need to check membership' or 'for writes, see post_board'. The agent is left to guess when 'zero-token pre-filtering' is appropriate.

    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 full burden. It mentions a '24h deposit' and 'Cloudflare Edge' but does not clarify what that means (e.g., temporary storage, deletion after 24h, payment implications, or side effects). No mention of mutations, permissions, or reversibility.

    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 one concise sentence that front-loads the core action while adding the key constraint (24h deposit) and location (Cloudflare Edge). 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?

    With 4 parameters (one nested object) and no output schema or annotations, the description provides insufficient context. It doesn't explain what 'deposit' means, the purpose of identity/intent_space, any auth requirements, or what happens after 24 hours. The description is too sparse for an agent to invoke safely without further inference.

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

    Parameters2/5

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

    Schema coverage is only 25% (payment_header has a description). The description does not explain domain, identity, or intent_space parameters, and only hints at 'deposit' which may relate to payment_header but not explicitly. The description fails to compensate for the low schema 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 ('Post a semantic intent board') and the target ('Cloudflare Edge'), distinguishing it from the sibling tool 'match_board' by its verb and resource. The purpose is specific and unambiguous.

    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 the tool is used for posting a board, but provides no explicit when-to-use or when-not-to-use guidance, nor does it reference alternative tools like match_board. It is clear but lacks explicit usage directions.

    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

a2a-board-engine MCP server

Copy to your README.md:

Score Badge

a2a-board-engine 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/AGICoffe/a2a-board-engine'

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