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gemini-omni-mcp

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Server Quality Checklist

58%
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  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool has a distinct and clearly defined purpose: editing videos, generating videos, and checking session status. No overlap in functionality.

    Naming Consistency5/5

    All tool names follow a consistent pattern with the 'omni_' prefix and verb_noun construction (edit_video, generate_video, status).

    Tool Count5/5

    Three tools is appropriate for a focused video generation and editing server, covering the essential operations without unnecessary extras.

    Completeness4/5

    The tool surface covers generation, editing, and status checking. Missing operations like listing or deleting videos, but these are not core to the stated purpose.

  • 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
    • 2 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.

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  • 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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  "maintainers": [
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  ]
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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, and the description does not disclose behavioral traits such as safety (read-only), authentication requirements, or side effects. It only states the checks performed.

    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 a single sentence with no unnecessary words. It efficiently communicates the two checks the tool performs.

    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?

    The description covers the main purpose but is incomplete without an output schema or mention of return values, which would help an agent understand what to expect.

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

    Parameters4/5

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

    There are zero parameters, so schema coverage is trivially 100%. The description does not need to add parameter meaning, and the baseline for 0 parameters is 4.

    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?

    Description uses a specific verb 'Check' and explicitly names two resources: 'Gemini session signed in' and 'generation in progress'. It clearly distinguishes from sibling tools omni_edit_video and omni_generate_video which perform actions.

    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 using this tool to check status before performing generation or editing, but it does not explicitly state when to use it vs. alternatives or when not to use it.

    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?

    No annotations are provided, so the description carries the full burden. It discloses that the tool keeps characters, physics, and scene continuity, which is a key behavioral trait. However, it does not mention side effects (e.g., overwriting original), required permissions, rate limits, or performance characteristics. The description is somewhat transparent but incomplete for a mutation tool.

    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 key purpose, and every sentence contributes value. It includes a reference to external documentation without fluff. Efficient and clear.

    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?

    Given the complexity of editing a video with AI and no output schema, the description covers the core action and change format but lacks details about output (e.g., format, file location), input video requirements (e.g., must exist), and potential limitations. It references GUIDE.md, but the description itself is somewhat incomplete.

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

    Parameters4/5

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

    Schema coverage is 100%, baseline is 3. The description adds value to the 'change' parameter by specifying the required phrasing format (one change, restate what stays the same, then the change). This clarifies how to use the parameter beyond the schema's description. The other parameters ('source', 'timeoutSeconds') are not further elaborated.

    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 edits an existing video using Gemini Omni, preserving characters, physics, and scene continuity. This distinguishes it from siblings: omni_generate_video (generates new videos) and omni_status (checks status). The verb 'edit' and resource 'video' are specific.

    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 a clear format for describing the change: 'ONE change in plain language. Restate what stays the same, then the change.' It also references GUIDE.md for more details. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.

    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. Discloses that the tool returns a local file path and requires an interview process. Does not mention error handling or permission needs, but overall transparent for a generation tool.

    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?

    Compact single paragraph with no redundant sentences. Purpose, warning, usage instructions, and output are all present and front-loaded.

    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?

    Covers main use case ('generate a video') and input options. Does not specify behavior when both `prompt` and `brief` are provided or error handling. Nested object schema is well-explained in description. Output is stated. Lacks edge case details but sufficient for typical use.

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

    Parameters4/5

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

    Schema coverage is 100%, but description adds context: explains the relationship between `prompt` and `brief`, the interview process, and the importance of not passing a raw one-liner. Enhances schema understanding.

    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?

    Starts with 'Generate a video with Gemini Omni'—specific verb+resource. Distinguishes from sibling tools (omni_edit_video, omni_status) by focusing on generation. Also mentions returning a local file path, clarifying the outcome.

    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?

    Explicitly instructs to run the creation interview in GUIDE.md first, then pass either a fully-formed `prompt` or a filled `brief`. Advises against passing a raw one-liner. Implicitly differentiates from edit/status tools via sibling names.

    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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