leaflet-mcp-server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool targets a distinct aspect of Leaflet map creation: adding markers, popups, layers, choropleth, GeoJSON, map initialization, coordinate conversion, debugging, and documentation search. No two tools have overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun snake_case pattern (add_, convert_, create_, debug_, search_, suggest_), making it easy to predict functionality.
Tool Count5/5
10 tools is well-scoped for a Leaflet code generation server. It covers core map creation, various layer types, data visualization, coordinate conversion, debugging, and plugin search without being overwhelming.
Completeness4/5
The tool set covers common map operations, but missing tools for custom tile layers, map interaction events (click, zoom), and layer removal. However, the core CRUD and lifecycle for map objects are present.
Average 3.4/5 across 10 of 10 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 status not available
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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 present, and the description fails to disclose behavioral traits such as whether the tool is read-only, what side effects exist, or what the generated code does. The description is too minimal to inform the agent about behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words. It is front-loaded and concise, though it omits important details.
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?
Given the tool has 4 parameters (one required) and no output schema, the description is too incomplete. It does not explain what 'Generate code' means, what format the output takes, or how the parameters interact. The tool's context within a code-generation library is only hinted by sibling names.
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% with descriptions for all parameters. The description adds no additional meaning beyond stating 'various options and content', which is already implied by the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description specifies 'Generate code for creating and customizing Leaflet popups', which clearly indicates the tool's purpose and resource. It distinguishes from siblings like add_marker by focusing on popups.
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 alternatives. It does not mention prerequisites, exclusions, or suggest other tools like add_marker for attaching popups to markers.
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?
No annotations are provided, so the description bears full responsibility. It does not disclose that this is a read-only help tool, nor does it describe the output format or any limitations. The description is too vague about what the agent can expect.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
One sentence with examples, no filler. Efficient but could be slightly expanded for clarity without becoming verbose.
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?
No output schema exists, and the description does not explain what the tool returns (e.g., troubleshooting steps, links, code snippets). This lack of information makes the tool less usable for an agent expecting a clear result.
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%, so baseline is 3. The description adds context by listing example issues that correspond to enum values, but it does not explain the 'description' parameter's format or provide additional guidance beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool provides debugging help for common Leaflet issues, with specific examples. It implicitly distinguishes from sibling tools (which focus on creation/configuration), though not explicitly.
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?
No explicit guidance on when to use this tool versus alternatives. Usage is implied by the description, but no exclusions or alternative tool suggestions are provided.
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 behavioral disclosure. It indicates the tool generates code, but does not explain the output format, side effects (e.g., does it require an existing map?), or any error conditions. This is insufficient for an agent to understand the tool's behavior fully.
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, concise and front-loaded with the main action. No extraneous information is present, and it efficiently communicates the tool's purpose.
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?
Given the absence of an output schema and annotations, the description should be more complete. It fails to explain what the tool returns (e.g., a code snippet) and lacks context about prerequisites or interactions with other tools. For a tool with 5 parameters, this is insufficient.
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 provides full parameter descriptions (100% coverage), so the baseline is 3. The description adds value by grouping optional features (popups, tooltips, custom icons) but does not provide additional semantic details beyond what is in 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 clearly states the tool's purpose: generating code for adding markers to a Leaflet map, with optional features like popups, tooltips, and custom icons. It uses a specific verb ('generate code') and resource ('adding markers'), and the distinction from sibling tools like add_popup is evident.
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?
The description provides no guidance on when to use this tool versus its siblings. It does not mention prerequisites, limitations, or alternative use cases. For example, it does not clarify that this tool is for markers, while add_popup might be for standalone popups.
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?
Annotations are absent, so description must disclose behavior fully. It states 'generate code' but does not explain output format, side effects, or permissions needed. Minimal behavioral insight beyond purpose.
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?
Single sentence that concisely states tool purpose with no redundant information. Front-loaded and efficient.
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?
With 5 parameters, no output schema, and no annotations, the description is too brief. It does not explain return values, code generation type (e.g., HTML/JavaScript), or any constraints. Incomplete for agent decision-making.
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 has 100% coverage with descriptions for all 5 parameters. Description adds no new meaning beyond 'color scales and legends', which is already implied by the schema. Baseline 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?
Description clearly specifies the tool generates code for an interactive choropleth map with color scales and legends, distinguishing it from siblings like create_layer or add_marker.
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 on when to use this tool versus alternatives (e.g., search_examples, suggest_plugin). No mention of prerequisites or context.
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?
No annotations provided, so the description must carry the burden. It states 'Generate code' implying a read-like operation, but doesn't disclose whether any state changes occur, permissions needed, or side effects. This is insufficient for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the core purpose efficiently. It is front-loaded with the action and resource. However, it could be slightly more structured with bullet points for clarity.
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?
Given the tool's complexity (6 parameters, nested objects, no output schema), the description is too brief. It doesn't explain parameter interdependencies (e.g., center and radius need layerType=circle) or return format. Incomplete for effective use.
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% with descriptive parameter names and comments. The description adds 'various Leaflet layers' but no extra semantics beyond the schema. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool generates code for creating Leaflet layers, listing specific types (polylines, polygons, circles, etc.). It distinguishes from sibling tools like add_marker or create_geojson_layer by focusing on vector layers.
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?
No explicit guidance on when to use this tool versus alternatives. The description implies it's for vector layers, but lacks context on prerequisites or exclusions, leaving the agent to infer from sibling names.
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 disclose behavioral details. It mentions includes tile layer setup and configuration, but does not clarify side effects (e.g., if it modifies existing code), output format, or behavior on missing parameters. This lack of detail hinders understanding of 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that efficiently communicates the tool's purpose. It is front-loaded and contains no redundant information.
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?
For a code generation tool with no output schema, the description is adequate but lacks details on output format (e.g., returns a string of code) and what 'complete' entails. It covers basic functionality but could be more thorough given the absence of 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 coverage is 100%, so parameters are well-documented in the schema. The description adds minimal additional meaning beyond what the schema provides (e.g., 'includes tile layer setup'), but does not offer extra semantic context for 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 clearly states it generates Leaflet map initialization code with HTML, CSS, and JavaScript. It specifies the resource (complete map initialization) and the verb (generate), distinguishing it from sibling tools like add_marker or create_choropleth that serve different purposes.
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 use for initializing a new Leaflet map, but does not explicitly state when to use it versus alternatives, nor does it provide conditions or exclusions. Guidance on sequencing with sibling tools (e.g., adding markers after map creation) is absent.
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?
No annotations provided, so description must disclose behavioral traits. It mentions validation but doesn't specify behavior on invalid input (e.g., error handling), rate limits, or any side effects. Minimal disclosure beyond core functionality.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence is concise and includes both conversion and validation aspects. No wasted words, but could be broken into separate sentences for clarity. Suitable for a simple tool.
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 only two parameters and no output schema, the description covers purpose and key formats. However, it lacks details on return values, error handling, or coordinate system assumptions, which are useful for a conversion tool.
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%, so baseline is 3. Description adds 'validate coordinates' which is not in the schema, providing additional context. However, it doesn't elaborate on input format specifics beyond what schema already implies.
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 clearly states the tool converts between coordinate formats and validates coordinates, which is a specific verb and resource. It distinguishes from sibling tools like add_marker or create_map, which serve different purposes.
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?
No explicit guidance on when to use this tool versus alternatives. However, sibling tools are clearly different (map creation, markers), so context implies usage for coordinate conversions. Lack of exclusions or prerequisites keeps it at mid-range.
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 exist, so the description bears full responsibility. It discloses the tool generates code but does not detail the output format (e.g., string, file), whether it is idempotent, or any side effects. It states 'generate code' which implies a read-only, non-destructive action, but more specificity is needed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's purpose. It has no filler words but could be slightly expanded (e.g., indicating the output type) without losing conciseness.
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 5 parameters (none required), nested objects, and no output schema, the description adequately explains the overall functionality. However, it lacks information on what the generated code looks like or how the returned data is structured, which would aid agent understanding.
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 context about 'custom styling and interactions' which aligns with parameters like style, onEachFeature, and filter, but it does not elaborate on parameter usage beyond what the schema already provides.
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 'Generate code' and the resource 'loading and displaying GeoJSON data on a Leaflet map with custom styling and interactions'. This distinguishes it from sibling tools like create_choropleth (specific to choropleth) and create_layer (more generic).
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 for GeoJSON data with styling and interactions but lacks explicit guidance on when to use this tool versus siblings such as add_marker, create_choropleth, or create_layer. No when-not or prerequisite information is provided.
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?
No annotations are provided, so the description carries full burden. It fails to disclose any behavioral traits, such as result format, pagination, rate limits, or whether it queries an external API.
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 concise sentence that front-loads the purpose with no wasted words.
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?
For a simple search tool with two parameters and no output schema, the description is minimally adequate but lacks information about return format or result structure.
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 baseline is 3. The description adds no parameter-specific details beyond what the schema already provides.
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 clearly states verb 'Search through' and specific resource 'official Leaflet examples and documentation', differentiating it from sibling tools which are all map-related actions.
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 this is the tool for finding examples and documentation, and no sibling tool serves a similar search function. However, it does not specify when not to use it or provide alternative names.
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 present, so the description bears full responsibility for behavioral disclosure. It states it 'gets recommendations' but does not specify whether the operation is read-only, how recommendations are generated, or any constraints (e.g., limited to known plugins). The minimal description does not fully compensate for missing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently conveys the tool's purpose with no unnecessary words. Every word earns its place.
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 low complexity (2 parameters, no output schema, no nested objects), the description is largely complete in stating what the tool does. However, it could be improved by briefly indicating the type of response (e.g., 'returns a list of plugin names and descriptions') to set agent expectations.
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%, with both parameters (functionality and category) having clear descriptions in the schema. The description adds no additional meaning beyond 'based on desired functionality or use case.' Since schema coverage is high, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get recommendations for Leaflet plugins based on desired functionality or use case.' It uses a specific verb ('Get recommendations') and resource ('Leaflet plugins'), and the purpose is distinct from sibling tools like add_marker or create_map, which perform actions rather than providing recommendations.
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 scenarios (when you need plugin recommendations based on functionality or use case) but lacks explicit guidance on when not to use it or alternatives. No exclusion criteria or comparison to sibling tools is provided.
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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