Skip to main content
Glama
vedantparmar12

Sticky Notes MCP Server

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v0.1.0

  • Disambiguation5/5

    Each tool serves a clearly distinct purpose: adding to the note file, reading all notes, creating a new notes file, and deleting all notes. No two tools perform the same action, so an agent can confidently select the right one.

    Naming Consistency4/5

    Tool names follow a mostly consistent verb-noun pattern (add_note, read_notes, delete_notes). The exception is save_to_new_file, which has a more complex verb-phrase structure, but it still uses the same snake_case style and starts with a verb, so the overall pattern remains readable.

    Tool Count5/5

    Four tools is well-scoped for a sticky notes server: one to add, one to read, one to delete, and one to save to a new file. Each tool earns its place without unnecessary bloat.

    Completeness2/5

    The set is missing essential operations for managing individual notes. There is no way to update a specific note or delete a single note, forcing users to delete all notes and re-add the ones they want to keep. This is a significant gap for a note-taking tool.

  • Average 4/5 across 4 of 4 tools scored. Lowest: 3.3/5.

    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 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.

  • 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?

    With no annotations, the description carries the burden of behavioral disclosure. It mentions returning a confirmation message but does not clarify what happens if the file already exists, whether permissions are needed, or other side effects. The description is too sparse to fully inform the agent.

    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 and well-structured. It front-loads the purpose in a single sentence, then uses Args and Returns sections for clarity. No unnecessary information is included.

    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 and has an output schema, so basic coverage is adequate. However, it omits important edge-case behavior (e.g., behavior if the file already exists, relationship to add_note). For a file creation tool, this is a moderate gap given no annotations.

    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 descriptions are empty (0% coverage), so the description's Args section provides some added meaning: filename is 'name of the new file to create' and content is 'content to save in the new file.' This goes beyond the bare schema types but lacks constraints, formats, or examples.

    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 action: 'Save content to a new notes file.' The word 'new' differentiates it from siblings like add_note, which may imply adding to an existing note. The verb+resource is 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 Guidelines2/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    No guidance is provided on when to use this tool versus alternative sibling tools. It only describes what the tool does without indicating scenarios, prerequisites, or exclusions. Users must infer from the name and sibling list.

    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 of behavioral disclosure. It reveals the append semantics (preserving existing notes) and the return type (confirmation string), but does not cover potential failure modes, file prerequisites, or permission needs. This is adequate but not exhaustive.

    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 compact and front-loaded with the primary purpose. The Args and Returns sections are clear and every sentence contributes necessary information without 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?

    The tool is simple with one parameter and an output schema. The description covers purpose, parameter, and return value. It could mention whether the file must exist or if it is created, but this lack is minor given the tool's straightforward nature and the presence of an output schema.

    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?

    The schema provides only the parameter name and type, with no description. The description adds full semantics by stating 'message (str): The note content to be added,' which clearly explains the parameter's meaning and role. This fully compensates for the zero schema description coverage.

    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 states a specific action ('Append a new note') on a specific resource ('the sticky note file'). This clearly distinguishes it from siblings like read_notes, delete_notes, and save_to_new_file, as it modifies an existing file rather than reading, deleting, or saving to a new file.

    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 usage through the action 'Append a new note' but does not explicitly mention when to use this tool versus its siblings. There is no guidance on alternatives or when not to use it, leaving the context to be inferred.

    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 the destructive action ('Delete all notes') and the return type (confirmation message), but it does not explicitly state permanence, non-reversibility, or any side effects like file modification. The behavior is clear but lacks extra 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 extremely concise: one sentence for the action plus a return spec. Every word is purposeful, and it is front-loaded with the main verb and resource. No wasted content.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

    The tool is simple with no parameters and an output schema (implied by the return description). The description fully explains what the tool does and what it returns, leaving no ambiguity. Sibling tools do not require additional disambiguation for this straightforward delete operation.

    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 0 parameters, so the baseline is 4. The description adds no parameter information because there are none. This is a perfect score for a parameterless tool.

    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 specific verb 'Delete' and resource 'all notes from the sticky note file', distinguishing it from sibling tools like add_note and read_notes. It is unambiguous and focused on a single, well-defined action.

    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 intended use is implied by the description ('Delete all notes'), but there is no explicit guidance on when to use this tool instead of alternatives, nor any mention of exclusions or prerequisites. Context makes it obvious for deletion, but the description does not provide explicit usage scenarios or comparisons.

    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 disclosing behavior. It clarifies the return type, line-break separation, and the default message when no notes exist. The read-only nature is implicitly disclosed by the verb 'Read', and no side effects are mentioned, which is adequate for a simple read tool. However, it does not address error conditions (e.g., missing file) or whether any implicit file creation occurs.

    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 remarkably concise and well-structured. It opens with the primary purpose, then provides a clearly separated 'Returns' section that explains the output format and a fallback case. Every sentence adds value, and there is no redundant or extraneous text.

    Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

    Completeness5/5

    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), the description is complete: it states what the tool does, what it returns, and how it handles an empty notes file. The existence of an output schema further reduces the need to explain return values in depth, but the description still provides useful details. The sibling tool names frame its niche as a read operation.

    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 schema provides no meaningful descriptions. The baseline for zero parameters is 4, and the description does not need to explain any because there are none. The return behavior is described, which partially compensates for the lack of 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 uses a specific verb ('Read and return') and identifies the resource ('all notes from the sticky note file'). It clearly distinguishes from sibling tools like add_note, delete_notes, and save_to_new_file by indicating a read-only operation with no modifications.

    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 its usage context (when you need to view all notes) but does not explicitly state when to use it over alternatives or mention any exclusions. It provides no direct comparison to sibling tools, leaving usage somewhat inferred rather than explicit.

    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

Sticky-notes-MCP MCP server

Copy to your README.md:

Score Badge

Sticky-notes-MCP MCP server

Copy to your README.md:

Latest Blog Posts

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/vedantparmar12/Sticky-notes-MCP'

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