Google Calendar MCP Server
Server Quality Checklist
Latest release: v0.1.4
- Disambiguation4/5
The three tools have clearly distinct purposes: retrieving events for a specific date, listing upcoming events, and searching by keyword. Some overlap exists (e.g., upcoming events could be retrieved by date), but the descriptions differentiate them well.
Naming Consistency5/5All tool names follow a consistent verb_noun pattern with snake_case: get_events_for_date, get_upcoming_events, search_events. The pattern is predictable and easy to understand.
Tool Count2/5With only 3 tools, the server feels under-scoped for a calendar service. Most calendar servers provide create, update, delete, and calendar management operations, which are missing here.
Completeness2/5The server only covers read/query operations (get, list, search). It lacks any write operations (create, update, delete events) or calendar management, leaving significant gaps for common workflows.
Average 3.8/5 across 3 of 3 tools scored.
See the Tool Scores section below for per-tool breakdowns.
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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 provided, so the description carries the full burden. It does not disclose any behavioral traits beyond the basic read operation, such as auth requirements, rate limits, or whether the calendar event list includes all-day events. It merely restates the function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise with no unnecessary words. It uses a structured format (Args/Returns) that is easy to scan. Every sentence is necessary.
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?
Given the simplicity of the tool (2 parameters, no nested objects), the description provides adequate information. However, it could include details like timezone handling or the format of the returned events list, though the output schema is available to supplement. Overall, it is minimally sufficient.
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 add value for parameters. It specifies the date format (YYYY-MM-DD) and the default for calendar_id. However, it does not explain the meaning of the parameters beyond what the schema already provides (type string). This is minimal but 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 'Get calendar events for a specific date', which is a specific verb+resource. Sibling tools 'get_upcoming_events' and 'search_events' are distinguished by the focus on a single date.
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?
No explicit when-to-use or when-not-to-use guidance is provided, but the purpose is clear enough that an agent can infer usage. Without differentiating advice like 'for a range of dates use search_events', the score is average.
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?
The description discloses the return format (formatted list with start time and title) but does not mention any behavioral traits such as read-only nature, permissions, or limitations. With no annotations, more detail would be beneficial.
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 concise, using a clear docstring format with Args and Returns sections. Every sentence serves a purpose without 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?
For a simple tool with two parameters and an output schema, the description covers purpose, parameters, and return. It could clarify 'upcoming' but is largely complete for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, but the description fully explains both parameters (max_results and calendar_id) along with their defaults, adding significant value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it retrieves upcoming calendar events, which is a specific verb-resource pair. However, it does not explicitly differentiate from siblings like get_events_for_date, leaving some ambiguity.
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?
No guidance is provided on when to use this tool versus the sibling tools (get_events_for_date, search_events). The agent is left to infer usage context from the name alone.
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 must carry the burden. It states the tool returns 'Matching events with start time and title', which is basic behavioral info but lacks details on read-only nature, rate limits, pagination, or error handling.
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 concise paragraph with clear Args/Returns sections. Every sentence adds value, no fluff or repetition.
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?
The tool has an output schema, so return values are partly covered by the schema. The description adds detail on returned fields (start time, title) and parameter defaults. However, it lacks information on sorting behavior or results ordering, which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description's Args section fully explains each parameter: query as search term, max_results with default, calendar_id with default. This adds critical 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 states 'Search calendar events by keyword', which is a specific verb+resource and distinguishes the tool from siblings like get_events_for_date or get_upcoming_events that are date-based.
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 for keyword-based searching but does not explicitly mention when to use it versus alternatives or when not to use it. No exclusions or alternative tool names are given.
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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