MCP Notes Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool has a distinct purpose: listing, reading, searching, creating, and appending. There is no overlap or ambiguity between the operations.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern in snake_case. Collection-level operations use plural (list_notes, search_notes) while single-item operations use singular (read_note, create_note, append_to_note), which is a clear and predictable convention.
Tool Count5/5With 5 tools, the server is well-scoped for a notes management purpose. Each tool covers an essential operation without unnecessary bloat.
Completeness3/5The server provides create, read, list, search, and append, but it lacks a delete operation and does not support full overwrite updates. These are notable gaps for a notes domain, limiting the completeness of the tool surface.
Average 4/5 across 5 of 5 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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 MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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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?
With no annotations, the description carries the behavioral disclosure burden. It adds one useful detail ('safe filename derived from its title'), but does not mention other behaviors such as handling of duplicate titles, whether content is required, or error conditions.
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, focused sentence with no redundant words. It front-loads the core action and includes a key detail, making it highly concise and readable.
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 create tool with an output schema and two parameters, the description covers the main purpose and a notable behavior. It does not explicitly guide against using append_to_note, but the name and description imply the difference. Missing details like overwrite behavior are not critical for basic invocation.
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?
The description explains the role of 'title' in filename generation, adding meaning beyond the schema. However, it says nothing about the 'content' parameter, leaving its purpose to schema inference. Given the 0% formal schema description coverage, partial compensation is acceptable.
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 creates a Markdown note, with a specific detail about filename derivation from the title. It distinguishes itself from sibling tools (list, read, search, append) by being the creation operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not mention when to use this tool versus alternatives like append_to_note, nor does it state any prerequisites or exclusions. It relies solely on the name and implied purpose.
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 full responsibility for disclosing behavioral traits. It states 'append' (implying mutation) and 'existing' (implying no creation), but it omits important side effects such as whether the file is modified in place, error behavior for non-existent files, or any permissions required. The description is too minimal to fully disclose the tool's behavior.
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, front-loaded sentence that communicates the core action and target without any filler. Every word contributes to the meaning.
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 append operation with two string parameters, the description, combined with the schema, conveys the essential information: it appends to an existing workspace-relative Markdown note. It does not explain return values (though an output schema exists) or error conditions, but the low complexity of the tool means these are less critical. The description is largely sufficient for correct invocation.
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 0%, so the description must compensate. It provides some clarification: 'workspace-relative' hints at the expected format for filename, and 'text' clarifies the nature of content. However, it does not explain details like whether content is appended with a newline or how filename path resolution works. The compensation is partial but adequate for simple string parameters.
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 ('Append text') and the target resource ('an existing workspace-relative Markdown note'). This is specific and distinguishes it from sibling tools like create_note (create new), read_note (read), and search_notes (search).
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 implies when to use the tool: when you need to add text to an existing note. The word 'existing' signals a precondition and implicitly contrasts with create_note, but it does not explicitly mention alternatives or scenarios where this tool should not be used (e.g., for overwriting content). Clear context without explicit exclusions.
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 that the tool returns snippets, implying a read-only nature, but it does not explicitly state whether it modifies data, how it handles no matches, or any other edge behavior.
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, front-loaded sentence with no filler words. Every word contributes to meaning, and it is appropriately sized for the tool's simplicity.
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 one parameter and an output schema, the description covers the core purpose and output behavior (snippets). It lacks explicit usage guidance, but the tool is simple enough that this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so the description must compensate. It explains that 'query' is used to search titles and contents, adding meaning to the bare parameter name. However, it does not provide constraints, formatting, or example values.
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 uses a specific verb ('Search') and resource ('note titles and contents'), and clarifies the result format ('short matching snippets'). This clearly distinguishes it from sibling tools like list_notes, read_note, create_note, and append_to_note.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (when you need to search notes), but it does not explicitly state when to use this tool versus alternatives like list_notes or read_note, or mention any exclusions.
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 provided, the description carries the burden of behavioral disclosure. 'List' clearly indicates a read-only operation, and specifying the output fields (titles and paths) adds useful context. It does not mention possible limitations or sort order, but for a simple zero-parameter tool, this is sufficient.
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 with no redundancy. It is front-loaded with the action verb 'List' and concisely states the resource and output details. Every word earns its place.
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 listing tool with no parameters and an output schema, the description is complete. It clearly states what is returned (titles and workspace-relative paths), and with an output schema present, no further detail on return values is needed. The tool's simplicity means nothing is missing.
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 zero parameters, and the schema coverage is trivially 100%. The description need not explain parameters, and per the rubric, a baseline of 4 applies for tools with no parameters.
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 uses the specific verb 'list' with the resource 'notes' and specifies the output scope as 'titles and workspace-relative Markdown paths.' This clearly distinguishes it from siblings like read_note (which reads content), search_notes (which searches), and create_note/append_to_note (which modify).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage by stating the tool enumerates note titles and paths, but it does not explicitly discuss when to use this tool versus the alternatives. There are no exclusions or specific context given, so it stays at an implied level.
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 are provided, so the description carries the responsibility for disclosing behavior. The word 'read' clearly indicates a non-destructive operation, and 'by workspace-relative filename' specifies the addressing scheme. It does not discuss error handling or return format, but the presence of an output schema covers return structure. This is adequate for a simple read 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 is a single sentence, directly communicates the action, and contains no filler. It is perfectly structured with the verb first and the qualifier last.
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 read operation with a single parameter and an output schema, the description provides all essential information: what it does (reads one note), which parameter to use (filename), and how it is interpreted (workspace-relative). It is complete enough for an AI to invoke correctly without extra documentation.
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?
The schema only defines 'filename' as a string with no description. The description adds crucial semantics by specifying that the filename is 'workspace-relative', which clarifies the expected input format. This helps the agent construct the correct argument value.
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 uses the specific verb 'read' plus resource 'one Markdown note' and specifies the key qualifier 'workspace-relative filename', which clearly differentiates it from sibling tools like list_notes (listing) and search_notes (searching). It precisely identifies the function without ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage: you should use this tool when you have the workspace-relative filename and want to retrieve a single note's content. However, it does not explicitly mention when not to use it or compare it with alternatives, such as suggesting search_notes when the filename is unknown. So it relies on context.
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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