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Avatarsia

OpenXE MCP Server

by Avatarsia
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TypeScript
Hybrid

Server Quality Checklist

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

  • Latest release: v0.1.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: 'openxe-discover' lists available actions, while 'openxe' executes them. There is no ambiguity.

    Naming Consistency2/5

    Tool names are inconsistent: 'openxe' is a generic name without a verb, while 'openxe-discover' adds a verb. No consistent verb_noun pattern is followed.

    Tool Count2/5

    With only 2 tools for a complex ERP system, the count is too low. The main 'openxe' tool bundles many unrelated actions, which should be separate tools.

    Completeness3/5

    The tool surface covers listing and retrieving documents like invoices and orders, but missing create, update, and delete operations. Some coverage exists but significant gaps remain.

  • Average 4.2/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 10 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

  • 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.

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    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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?

    Annotations indicate destructiveHint=true, but the description does not disclose which actions are destructive or warn about potential side effects. It lists examples mostly read-only (list, get, dashboard) but the action parameter is open-ended, leaving the agent uninformed about destructive behaviors.

    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 long but well-organized with headings, bullet points, and examples. Almost every line adds useful information, though a bit more brevity could be achieved without losing clarity.

    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?

    Despite no output schema, the description explains return formats (json, table, csv, csv-positions, ids) with detail on csv-positions, and covers the where filter syntax thoroughly. It does not address error handling or nonexistent actions, but for the complexity of the tool it is reasonably complete.

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

    Parameters5/5

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

    Schema coverage is 100%, but the description adds substantial value by explaining the structure of the 'params' object with concrete sub-parameters (format, zeitraum, where, status_preset), their possible values, and usage examples. This goes far beyond the schema's vague 'tool-specific parameters'.

    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 executes OpenXE ERP actions (Fuehrt eine OpenXE-Aktion aus) and distinguishes it from the sibling openxe-discover tool, which is for listing actions.

    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 explicitly instructs to call openxe-discover once per session to get the action list, providing clear when-to-use guidance relative to the sibling. It could be more explicit about when not to use the tool, but the alternative is well defined.

    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?

    Annotations already indicate readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds the behavioral constraint of calling only once per conversation, which is valuable context beyond the annotations. No contradictions.

    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 three sentences long, front-loaded with the core purpose, and wastes no words. Every sentence adds value: purpose, usage frequency, sibling reference, and parameter note.

    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 (one optional parameter, no output schema), the description is nearly complete. It could mention that the output is a list of available actions, but the purpose implies that. The guidance on when to call and the sibling reference are sufficient for an agent to use the tool correctly.

    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% and the parameter 'category' is already fully described with enum values and default. The description only mentions an optional category filter without adding new meaning, so it meets the baseline but does not exceed.

    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 shows available OpenXE actions and specifies when to call it (once at conversation start). It distinguishes itself from the sibling 'openxe' tool by indicating that 'openxe' is for executing actions, making the purpose very clear.

    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?

    The description explicitly provides usage guidance: call once at conversation start, do not call more than once, and use the sibling 'openxe' tool for execution. This leaves no ambiguity about when and how to use this tool.

    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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