VNDB MCP Server

Server Quality Checklist

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

Latest release: v1.0.0
Disambiguation5/5
Each tool has a distinct purpose: searching, adding, removing, updating status, retrieving the user's list, and checking authentication. There is no meaningful overlap between them.
Naming Consistency5/5
All tool names follow a consistent snake_case verb_noun pattern (e.g., search_vn, add_vn_to_list, update_vn_status), with minor prepositions that do not break uniformity.
Tool Count5/5
Six tools cover the core operations of a VN list management server without being excessive or sparse. Each tool serves a clear, necessary function.
Completeness5/5
The set provides full lifecycle coverage for a user's VN list: search, add, remove, update status, and retrieve the list, plus authentication. There are no obvious gaps for the stated purpose.
Average 3.7/5 across 6 of 6 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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under ISC 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.
Add a glama.json file to provide metadata about your server.
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.
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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions changing the status and does not disclose that vote and notes can also be updated, that notes overwrite existing notes, or any permission or side-effect considerations. For a mutation tool, this is a significant 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 concise: one purpose statement followed by a helpful example. It is front-loaded, contains no filler, and every sentence earns its place.
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?
The tool has four parameters, no annotations, and no output schema. The description focuses only on status updates and omits the tool's broader capability to also set vote and notes. It does not mention return behavior or side effects, leaving the description incomplete relative to the tool's actual scope despite the schema covering parameters.
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 description coverage is 100%, so the baseline is 3. The description adds a small semantic mapping with 'В процессе' and 'Завершено', but it does not explicitly map these to the enum values or clarify vote/notes usage. The schema itself handles most parameter meaning, so the description provides marginal added value.
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 'Изменяет' (changes) and the resource 'статус визуальной новеллы' (status of a visual novel) in the user's list. The example 'переместить из "В процессе" в "Завершено"' concretely illustrates the action, and the purpose is distinct from siblings like add_vn_to_list or remove_vn_from_list.
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 provides a concrete usage example ('переместить из "В процессе" в "Завершено"'), which implies when to use the tool, but it does not explicitly mention alternatives or when not to use it, such as adding a new entry with add_vn_to_list or removing one with remove_vn_from_list. Guidance is thus implied rather than fully explicit.
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 provided, the description must fully disclose behavioral traits. It does mention the notable two-step behavior (auto-search by name, then add), which is helpful. However, it omits other important details such as authentication requirements, failure modes (e.g., what happens if the VN is not found or already in the list), and whether the action is reversible or idempotent.
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 two sentences long and front-loaded with the core action. The second sentence adds useful behavioral context (automatic search) without any wordiness. Every phrase earns its place.
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 tool has 4 parameters, 2 required, and no output schema, and there are no annotations to fill gaps. The description covers the main action and behavior, but it does not mention what the tool returns, potential errors, or the need for authentication. Given the simplicity of the operation, the description is partially complete but leaves out transaction-level details that an agent would need for robust handling.
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 input schema covers 100% of the parameters with meaningful descriptions (vnName supports Russian names or IDs, status has enum with Russian translations, vote and notes are clearly explained). The description adds no additional parameter-level detail beyond the schema, so the baseline of 3 applies.
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: adding a visual novel to the user's VNDB list with a specified status. It also mentions the automatic search behavior, which distinguishes it from sibling tools like remove_vn_from_list or update_vn_status. The verb 'adds' and the resource 'visual novel to the list' are 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 use case (adding a new VN to the list), and the auto-search behavior provides some context. However, it does not explicitly state when to use this tool versus siblings like update_vn_status or search_vn, nor does it mention any exclusions or prerequisites (e.g., authentication).
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 provided, the description carries the full burden of behavioral disclosure. It only states a simple read operation, omitting details about authentication requirements, pagination via limit, error handling, or return format. This minimal description provides little beyond the basic function.
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 clear sentence with no redundant information. It is front-loaded with the action and resource, making it efficient and easy to parse.
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 low complexity (2 params, no output schema), the description provides the core purpose but omits behavioral details like pagination or output structure. It is minimally sufficient for a simple list retrieval, but lacks the context that would fully prepare an agent for response handling and usage limits.
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?
Both parameters are fully described in the schema, so the description adds nothing new about parameter meanings. Schema coverage is 100%, which meets the baseline for a score of 3.
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 retrieves a list of the user's visual novels filtered by status. The verb 'get' and resource 'list of visual novels' distinguish it from sibling tools like add, remove, update, and search.
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 for fetching the user's VN list with a status filter, but it does not explicitly differentiate from search_vn or provide exclusions. No alternative tools are mentioned, so usage context is only implied, not explicitly guided.
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 must disclose behavior, but it only states the basic removal action without mentioning auth requirements, irreversibility, or what happens if the VN is not in the list. This is insufficient context for a mutating 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 a single, clear sentence with an active verb and direct object, with no filler or redundancy. It 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.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, so the description covers the basic operation, but with no annotations or output schema, it lacks details on side effects, auth, or error behavior. It is minimally adequate but incomplete for a destructive operation.
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 schema already documents the single vnId parameter with an example, achieving 100% coverage, so the description does not need to add much. The description's wording adds no further parameter nuance beyond 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 uses the specific verb 'Удаляет' (removes) with the resource 'визуальную новеллу из списка пользователя', clearly distinguishing it from sibling tools like add_vn_to_list and update_vn_status. There is no ambiguity about what operation is performed.
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 does not explicitly state when to use this tool, but the purpose and sibling names imply it is for removing a VN from the user's list. No exclusions or alternatives are mentioned, only the action itself.
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 provided, the description carries the full burden. It discloses the tool's read-only intention (checking connection, getting user info) but does not mention error handling, failure behavior, or whether authentication is required. The description is adequate for a simple check but lacks deeper behavioral context.
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, front-loaded sentence that directly states the tool's action and purpose. Every word contributes to understanding, with no filler or redundancy.
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 (no parameters, no output schema) and its clear distinction from siblings, the description is largely complete. It could optionally mention what specific user information is returned or any failure modes, but the description sufficiently covers the core functionality for a basic auth check.
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?
The tool has zero parameters, so the baseline is 4. The description adds no parameter-specific meaning because there are none, but it also does not need to. It correctly omits any parameter discussion.
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: checking the connection to the VNDB API and retrieving current user information. This distinguishes it from sibling tools, which all focus on VN list management (add, remove, update, search), so there is no ambiguity about its role.
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 when to use the tool (to verify API connectivity and user identity), but it does not explicitly state when it should be used compared to alternatives. No exclusions or prerequisites are mentioned, though they are minimally relevant for a parameter-less auth check.
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, the description carries the full burden. It states that the tool searches and returns information, which implies a read-only operation, but it does not explicitly mention that it makes no changes, requires no authentication, or discuss what happens if no results are found. The Russian language support is a helpful behavioral detail, but overall the description gives only minimal behavioral disclosure.
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, well-structured sentence that front-loads the action and includes the key input types and scope. Every word contributes meaning, with no filler or repetition.
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?
The tool is simple with one param and no output schema, and the description covers the purpose and input format adequately. It mentions that results return information about found VNs, which is somewhat vague, but given the low complexity, the description is reasonably complete. It does not cover edge cases like empty results, but this is a minor gap.
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 description is thorough, covering both Russian names and ID formats. The description adds the VNDB context and return behavior, but it does not significantly enhance the parameter 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.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches for a visual novel on VNDB by title (with Russian support) or ID, which is a specific verb-plus-resource. It distinguishes itself from sibling tools, which are all list management and auth operations.
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 implies when to use this tool: when you need to find a VN by name or ID, possibly in Russian. It provides clear context but does not explicitly exclude alternatives or mention when not to use it. However, the sibling tools are obviously different, so usage context is reasonably clear.
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

Copy to your README.md:

[![vndb-mcp MCP server](https://glama.ai/mcp/servers/ivanmem/vndb-mcp/badges/card.svg)](https://glama.ai/mcp/servers/ivanmem/vndb-mcp)

Score Badge

Copy to your README.md:

[![vndb-mcp MCP server](https://glama.ai/mcp/servers/ivanmem/vndb-mcp/badges/score.svg)](https://glama.ai/mcp/servers/ivanmem/vndb-mcp)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/ivanmem/vndb-mcp'

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