vicsee-mcp-server
OfficialServer Quality Checklist
Latest release: v0.3.3
- Disambiguation5/5
Each tool targets a distinct function: generation, credits, task polling, model listing, file upload, and upscaling (image/video). No overlap in purpose.
Naming Consistency5/5All tools follow a consistent 'vicsee_verb_noun' pattern in snake_case, making them predictable and easy to distinguish.
Tool Count5/57 tools cover the core workflows (generation, upscaling, polling, listing, uploading, credits) without being excessive or sparse.
Completeness4/5The surface covers generation, upscaling, and account operations. Missing a cancel/delete task endpoint, but the core async workflow is fully supported.
Average 4.3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 33 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.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, indicating a safe, non-mutating operation. The description adds that it targets the 'configured API key', which is useful but does not disclose further behavioral traits beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loading the key action and resource. It contains no filler and is appropriately concise for the tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has no output schema, so the description should at least hint at the return format. It only says 'get...balance' without specifying response structure (e.g., numeric value, JSON object). This yields a moderate gap in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so schema coverage is 100%. The description does not need to add parameter semantics, and the baseline score of 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Get the current VicSee credit balance for the configured API key' with a specific verb (get) and resource (credit balance). It distinguishes from sibling tools like vicsee_generate or vicsee_list_models, which handle different tasks.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (checking credit balance). While no explicit exclusions or alternatives are given, the sibling tools are distinctly different, so the usage is straightforward.
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 signal readOnlyHint and openWorldHint, so the agent knows the tool is safe and non-destructive. The description adds useful context by stating the output includes capabilities and credit costs, and reaffirms the read-only nature. No contradictions or missing behavioral traits for a simple list tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences. The first clearly states the purpose, and the second provides a crucial usage hint and optional filter. Every word adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional param, no output schema), the description adequately covers the tool's role and output. It mentions that the output includes model id, capabilities, and credit costs. No mention of pagination or error cases, but for a straightforward listing tool, the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%; the only parameter 'type' is described in the schema as 'Filter by media type.' The description merely echoes this with 'Optionally filter by media type,' adding no new meaning beyond the schema. Baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool lists available VicSee models with their capabilities and credit costs. It also explicitly indicates that this should be called first to obtain a model ID for vicsee_generate, distinguishing it from sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit guidance to 'Call this first to find a model id to pass to vicsee_generate,' which is a strong when-to-use instruction. It also mentions optional filtering by media type, but does not provide explicit when-not-to-use or alternative tool scenarios, though sibling context makes alternatives clear.
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?
Adds asynchronous behavior beyond annotations (readOnlyHint=false indicates mutation; description clarifies it returns a task id). However, it does not disclose what happens to the original image or any side effects, and lacks authentication/rate limit details.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no extraneous information. Front-loaded with the core action and essential details about async behavior and default parameter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 parameters and no output schema, the description covers the key aspects: input format, async nature, default factor. It could elaborate on what the task response contains, but it directs to poll vicsee_get_task which suffices.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage but description adds value by stating the default value for 'upscale_factor' ("2") which is not in the schema. The description also reinforces the 'publicly accessible' constraint for image_url.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool upscales publicly accessible images, specifying supported formats (JPEG/PNG/WebP) and mentions asynchronous behavior, which distinguishes it from sibling tools like vicsee_upscale_video.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage guidance: async operation returns a task id to poll, and upscale_factor has a default of '2'. However, it does not explicitly state when not to use this tool or compare with 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 annotations indicating readOnlyHint=false and openWorldHint=true, the description adds context about async behavior, polling requirement, and constraints (public URL, format, duration). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences efficiently convey purpose, constraints, async behavior, and default. No unnecessary words, front-loaded with key information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, no output schema), the description covers essential aspects: input constraints, async flow, and parameter default. Does not mention error handling or rate limits, but those are less critical here.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already describes both parameters. The description adds the default value for upscale_factor ("2"), which provides additional value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (upscale), resource (video), and constraints (publicly accessible, MP4/MOV/MKV, up to 60s). It effectively distinguishes from sibling tool vicsee_upscale_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains the asynchronous nature and directs to poll vicsee_get_task for completion. It includes the default for upscale_factor, but does not explicitly state when not to use the tool.
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?
Description adds behavioral details beyond annotations: status enum values, result fields for completed/failed states, and polling recommendation. Annotations indicate read-only and open-world, which are consistent. 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no waste: first states purpose, second lists statuses and result structure, third provides polling guidance. Front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter, annotations, and no output schema, the description covers all needed context: status values, result/error handling, and polling frequency. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description restates the parameter's origin (from generate/upscale) but adds no new meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it polls a generation or upscale task by ID, specifies status values, and explains result/error fields. It distinguishes from sibling tools like vicsee_generate (creates tasks) and vicsee_upscale_* (creates tasks) by focusing on polling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells when to use (after generation/upscale) and to poll every few seconds until done. It does not explicitly list alternatives or when not to use, but the context from sibling tools makes it clear it's for polling only.
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?
Discloses asynchronous generation, immediate task id return, polling needed for result, and input format rules (public URLs, local paths, base64). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with logical sections (async, model selection, input types). Concise but not terse; every sentence adds value. Could be slightly more compact but effective.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive for a complex tool with 14 parameters: covers async behavior, polling, model selection, input formats, constraints for all model categories, and edge cases like video-edit audio settings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds valuable context: positional referencing for references, constraints on video/audio URLs, and explanation of audio_setting options.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Create an AI image or video with VicSee.' and distinguishes from siblings by mentioning async behavior, polling, and model selection using vicsee_list_models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit guidance for different model types (image-to-video, reference-to-video, video-edit) and input requirements. Does not explicitly list when not to use, but context is clear.
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 file uploads directly to storage and only public URL returns, plus warns about base64 truncation. Could add file size limits or supported formats, but still strong.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences plus a recommendation. No unnecessary words, front-loaded purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple upload tool with one parameter, description covers purpose, usage pattern, and behavior. Integrates well with sibling tools and explains return value (public URL) despite no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter (file_path). Description adds no additional semantic detail beyond the schema's 'absolute path' description, 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.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly describes uploading a local file (image, video, audio) and returning a public URL. Distinguishes from siblings by mentioning usage in vicsee_generate for reference_image_urls or image_urls.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly advises preferring this tool over inline base64 due to truncation risks, and specifies how the returned URL is used in vicsee_generate, providing clear when-to-use guidance.
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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