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JoeyBrar

AgentSeal

by JoeyBrar
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

83%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v0.2.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: record_action records, query_actions retrieves, verify_chain checks integrity. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern (query_actions, record_action, verify_chain), making them predictable and easy to understand.

    Tool Count5/5

    Three tools is an ideal scope for an audit trail server, covering the essential operations of recording, querying, and verifying without unnecessary bloat.

    Completeness5/5

    The tool surface fully covers the core lifecycle of an audit trail: recording actions, looking up history, and verifying chain integrity. No obvious gaps given the domain's immutability requirements.

  • Average 4.1/5 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 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.

  • This repository includes a glama.json configuration file.

  • 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.

  • View related servers

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

  • Behavior3/5

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

    No annotations provided, so the description carries the burden. It implies read-only behavior by saying 'look up', but does not explicitly state non-destructiveness, side effects, or permissions needed. It is adequate but could be more explicit.

    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?

    Two succinct sentences, front-loaded with the main purpose, no redundant information. Every sentence adds value.

    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 simplicity (3 optional parameters, no output schema), the description covers the main use. However, it omits details about the return format, which could aid agent understanding. Still, it is mostly complete.

    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%, so baseline is 3. The description does not add any extra meaning beyond what the schema already provides for each parameter. It is sufficient but not enhanced.

    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 verb 'look up' and the resource 'previously recorded actions from the audit trail'. It also lists use cases: 'check what actions have been taken, verify history, or recall past decisions'. This distinguishes it from siblings like record_action (write) and verify_chain.

    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?

    The description provides clear context on when to use the tool (check actions, verify history, recall decisions). However, it does not explicitly mention when not to use it or compare to alternatives, though siblings are distinct enough.

    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?

    With no annotations, description carries full burden. Mentions 'cryptographically sealed record' hinting at immutability, but does not disclose side effects, permanence, or system impact. Adequate for a simple append action, but could be more detailed.

    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?

    Two sentences efficiently convey purpose and usage. No extraneous information; every word adds value.

    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 complexity (5 params, nested objects, no output schema), the description covers purpose and usage well but omits mention of return value or additional behavioral context. Nearly complete.

    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%, so baseline 3. Description does not add extra parameter meaning beyond the schema; all parameters are already well-described in the schema.

    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 records actions to an audit trail, with specific verb 'Record' and resource 'agent action'. It distinguishes from siblings (query_actions, verify_chain) by focusing on recording, not querying or verifying.

    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?

    Explicitly advises calling 'after every significant action' with examples, providing strong when-to-use guidance. Lacks explicit when-not-to-use instructions but context with sibling tools implies alternatives.

    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?

    With no annotations, the description carries the full burden. It discloses the core behavior: verifies chain integrity, uses SHA-256, reports break location. However, it does not explicitly state whether the tool is read-only or has side effects, which is a minor gap.

    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: two sentences that efficiently convey purpose, mechanism, and behavior. No redundant or unnecessary information.

    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?

    For a simple tool with one optional parameter and no output schema, the description covers the key aspects: what it verifies, how it works, and what indicates tampering. It could optionally detail the output format (e.g., break location), but this is not essential for correct invocation.

    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?

    The description does not mention the agent_id parameter directly. However, the input schema already describes it clearly (100% coverage). The description adds no additional meaning beyond the schema, so baseline score of 3 is appropriate.

    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: 'Verify the integrity of the audit trail hash chain.' It explains the cryptographic mechanism (SHA-256 hash chain) and distinguishes itself from sibling tools (query_actions, record_action) by focusing exclusively on integrity verification.

    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?

    The description implicitly tells when to use this tool: when you need to detect data tampering via hash chain breaks. It does not explicitly state alternatives or when not to use, but the purpose is clear enough that an agent can infer appropriate usage.

    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 the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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