Calendly MCP Server

Server Quality Checklist

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

Latest release: v2.0.0
Disambiguation5/5
Each tool targets a distinct action or resource: auth (OAuth URL, token exchange, refresh), user info, events (list/get/cancel/schedule), event types (list/availability), invitees, and org memberships. There is no overlap or ambiguity between tools.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case, using clear verbs like get, list, cancel, exchange, refresh, and schedule. The naming is uniform and predictable.
Tool Count5/5
With 12 tools, the set is well-scoped for a Calendly integration. It covers authentication, user, events, event types, invitees, and org memberships without being bloated or sparse.
Completeness4/5
The toolset covers the full scheduling lifecycle (list event types, check availability, schedule, list/get/cancel events) and authentication. Minor gaps like rescheduling or updating events are missing, but core workflows are complete.
Average 3.3/5 across 12 of 12 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed 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

Behavior1/5
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. 'Cancel' implies a state change, but the description does not state whether cancellation is reversible, whether it deletes the event or marks it as canceled, whether it notifies attendees, or what conditions must be met (e.g., event ownership). This is almost no behavioral transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-specified rather than appropriately concise. It lacks the detail needed for a mutation tool, and the sentence essentially restates the tool name with little added value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of annotations and output schema, this description is severely incomplete. It does not explain side effects, prerequisites, return values, or edge cases (e.g., canceling a non-existent event). For a 2-param tool, the description provides only the basic purpose and leaves the agent with many unknowns.
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 parameters with descriptions: event_uuid is 'UUID of the event to cancel' and reason is 'Reason for cancellation'. The description adds no extra meaning beyond the schema, so the baseline of 3 applies. It does not clarify formats or optionality 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?
The description 'Cancel a specific event' uses a clear verb (cancel) and resource (event), and the specificity distinguishes it from siblings like schedule_event or get_event. However, it lacks any additional scope or clarification that would make it a 5, such as mentioning the event must already exist or that cancellation is permanent.
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 that this should be used for events created via schedule_event, nor does it exclude events that are already canceled or in the past. Without any context or alternatives, the agent receives no usage direction.
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?
There are no annotations to provide safety or read-only hints, so the description carries the full burden. It fails to disclose that listing is non-destructive, that multiple filters (status, time range, organization) are supported, or that user_uri can target other users; the 'authenticated user' claim is contradicted by the schema's user_uri parameter.
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 with no filler. It is front-loaded with the verb and resource and earns its place, though it may be slightly too brief.
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 six optional parameters, no output schema, and no annotations, the description is under-specified. It omits key details about filtering options, pagination, and the ability to list for other users via user_uri, which are critical for correct usage.
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 well-described parameters, so the baseline is 3. The description adds no additional parameter semantics, but the schema fully covers parameter meanings including defaults and formats.
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 clearly identifies listing scheduled events as its function and distinguishes it from sibling tools like get_event and list_event_types. However, the scope 'for the authenticated user' is slightly misleading given the optional user_uri parameter allows listing events for other users, so it's not fully precise.
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 siblings like get_event or schedule_event, nor any exclusions for when this tool should not be used. The description simply states what it does without contextual usage advice.
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 does not mention what happens on success or failure, whether the refresh token is rotated, if authentication is needed, or what the response contains. This is insufficient for a security-sensitive OAuth operation.
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 short sentence with no wasted words. It is front-loaded and easy to scan. However, it is slightly redundant ('refresh access token using refresh token'), which prevents a perfect score.
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?
There is no output schema, so the description should explain the return value (e.g., new access token, new refresh token) or indicate when to use it in the OAuth flow. It does neither, leaving the tool's behavior and response unclear. The minimal description is inadequate for a tool without annotations or output schema.
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 fully documents the single parameter (refresh_token) with a description, so schema coverage is 100%. The description's phrase 'using refresh token' adds no additional semantic value beyond what the schema provides, earning the baseline of 3.
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 clearly states the action ('Refresh access token') and the mechanism ('using refresh token'). It is specific and understandable, though it does not explicitly differentiate from sibling tools like exchange_code_for_tokens or get_oauth_url. The verb-resource pair is 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?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no context such as 'use when access token expires'. It is a bare statement without any usage context or exclusions.
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 the full burden. It implies a read-only listing operation, but discloses no details about authentication, pagination, rate limits, or response format. Minimal behavioral information beyond the statement itself.
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 with no 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?
Given the tool's simplicity and full schema parameter coverage, the description is minimally adequate. However, with no output schema and no annotations, it lacks details about return structure or filtering behavior, leaving some gaps for the agent.
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 all three parameters with descriptions (100% coverage), so the schema does the heavy lifting. The tool description adds no extra parameter meaning, warranting the baseline score of 3.
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 uses the verb 'List' with a specific resource 'event types' and adds context 'for scheduling meetings'. It is clear what the tool does, though it does not explicitly differentiate from sibling tools like list_events or get_event_type_availability.
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 gives no guidance on when to use this tool versus alternatives. It does not state any prerequisites or exclusions, leaving the agent to infer usage from the name and 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 are provided, so the description must disclose side effects. It only says 'creating an invitee,' failing to mention email sending, calendar mutations, required permissions, or other behavioral details expected from a scheduling tool.
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 concise sentence with no filler, though 'creating an invitee' is slightly awkward. It efficiently communicates the main action.
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 15 parameters, no output schema, and no annotations, this minimal description leaves many operation details (e.g., guest limits, location handling, UTM parameters) unexplained. The agent gets little guidance beyond the schema, so completeness is low.
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 parameters with descriptions, so the baseline is 3. The description adds only 'specific event type and time,' which does not meaningfully enhance understanding 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?
The description uses a specific verb ('schedule') and resource ('meeting by creating an invitee'), clearly distinguishing it from siblings like cancel_event and list_events. The phrase 'creating an invitee' is slightly awkward but understandable.
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 scheduling meetings but provides no explicit comparison to alternatives or conditions for when to use this tool over others. It relies on the reader to infer context from the name and siblings.
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 only states the basic listing action and scope—it does not mention authentication requirements, the default count of 20, pagination, filtering behavior, or the response format. This leaves significant behavioral details undisclosed.
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 conveys the tool's purpose. There is no filler or repetition. It is appropriately concise for a simple list operation, and every word contributes meaning.
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 description is minimal and does not mention return values, default behavior, or how the optional parameters influence results. With no output schema and no annotations, the description should provide more context about pagination, count defaults (20, max 100), and that it returns memberships of the authenticated user. The current description is incomplete for a tool with four optional parameters and no output schema.
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 all four parameters with descriptions (100% coverage). The tool description adds no additional parameter semantics beyond what the schema already provides. Baseline of 3 is appropriate because the schema does the heavy lifting and the description adds marginal 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 action ('List') and the resource ('organization memberships'), and specifies the scope ('for the authenticated user'). This is unambiguous and distinguishes it from sibling tools like list_events or list_event_invitees, which target different resources.
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 explicit guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. The only contextual hint is 'for the authenticated user,' which implies use case but does not compare with other tools or explain when this should be chosen over others.
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?
The description gives no behavioral disclosure beyond the verb 'get'. With no annotations, it does not state that the operation is read-only, safe, or any other traits, leaving the agent to assume the obvious but without explicit confirmation.
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 conveys the purpose without any filler or redundancy. 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?
For a simple read operation with one well-documented parameter, the description is adequate. It does not describe return structure, but the phrasing 'details' implies that. Without output schema or annotations, a bit more context could be useful, but it is largely complete for this trivial tool.
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 already fully documents event_uuid with the description 'UUID of the event to retrieve'. The tool description adds no additional meaning beyond 'specific event', which is already implied by the schema and tool name.
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 'Get details of a specific event' clearly names the verb (get) and resource (event), and the qualifier 'specific' distinguishes it from the sibling list_events. It is unambiguous about what the tool does.
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 like list_events or cancel_event. The description does not mention any context or exclusions for usage.
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 states the tool retrieves availability but does not clarify default time windows, timezone handling, or behavior when start_time/end_time are omitted. The read-only nature is implicit but not explicitly stated.
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, direct sentence with no redundant words. It is front-loaded with the key action and resource, making it highly concise.
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?
Without an output schema and annotations, the description should explain return format and parameter interdependencies. It fails to indicate whether a time window is required, what the response looks like, or how availability is calculated, leaving significant gaps for a tool with optional time 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?
The input schema provides 100% coverage with descriptions for all three parameters, so the description adds no additional meaning beyond what the schema already explains. The schema covers the event_type URI and ISO 8601 time formats.
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 identifies the action (get), the resource (available time slots), and the scope (for a specific event type). It distinguishes itself from sibling tools like schedule_event (which creates bookings) and list_event_types (which lists event type metadata).
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 verb 'get' and phrase 'available time slots' imply the tool is used to check availability before scheduling, but no explicit guidance is given about when to use it versus alternatives. There is no mention of exclusions or alternative tools.
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 'List invitees' but does not mention pagination, filtering, ordering, permissions, error behavior, or the structure of the returned list. For a read operation, it lacks context about what the agent should expect in terms of response and side effects.
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 is front-loaded with the action and resource. It contains no filler or redundancy, making it highly 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?
Although the schema covers all parameters, there is no output schema and no annotation. The description is too minimal to fully contextualize the tool: it does not state what the returned invitee list looks like, how pagination works, or any filtering/prerequisite details. Given the simple nature of the tool, more elaboration on return values and behavior would be expected.
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%, and each parameter (count, email, status, event_uuid) has its own description. The tool description itself adds no parameter-level meaning, but since the schema fully documents them, the 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 'List invitees for a specific event' uses a specific verb (List) and resource (invitees for an event), clearly distinguishing it from siblings like list_events or get_event by scoping to invitees of a particular event. It directly states the tool's 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need invitees of a particular event, but it does not explicitly mention when not to use it or provide alternatives among the sibling tools. There is no exclusionary guidance, so the context is only implicitly derived from the 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, the description carries the full burden of behavioral disclosure. It does not mention side effects, validation behavior, required external setup, or return format, leaving the agent without important context about how the tool behaves.
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 earns its place without redundancy. It is front-loaded with the action and resource, making it easy to parse quickly.
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 the description gives a clear basic purpose, but with no output schema and no annotations, the description should at least clarify that it returns the URL and note any relevant context (e.g., OAuth flow position). It is adequate but leaves gaps.
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 100% parameter coverage with descriptions for both parameters. The description adds no additional meaning beyond what the schema already states, so a 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 uses a specific verb ('Generate') and resource ('OAuth authorization URL'), clearly stating its purpose. It differentiates from siblings like exchange_code_for_tokens and refresh_access_token, which handle subsequent OAuth steps.
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 phrase 'for user authentication' implies the tool is used to start the OAuth flow. However, it provides no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites.
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 present, so the description must convey behavioral details. It mentions the output tokens but omits important behaviors like single-use code consumption or redirect_uri matching requirements, leaving the agent without critical execution 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?
A single, focused sentence with no filler. Perfectly sized for the simple exchange operation.
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 description covers the basic function but lacks details about OAuth flow placement, error conditions, and code expiry. While the schema covers parameters, the absence of an output schema and behavioral context leaves gaps for an agent.
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 cover both parameters with clear meanings (authorization code and redirect URI), so the tool description adds no additional semantics. Baseline score of 3 applies given high schema 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 clearly specifies the action (exchange) and the resource (authorization code for tokens). It distinguishes from siblings like get_oauth_url and refresh_access_token, which handle different parts of the OAuth lifecycle.
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 its use in the OAuth flow after obtaining a code, but does not explicitly state when not to use it or mention that refresh_access_token is for later token renewal. Context is clear but lacks 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, the description carries full disclosure burden. It states this retrieves user information but does not specify authentication requirements, return format, or potential errors. The term 'authenticated' hints at auth context, but lacks further behavioral detail.
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 wastes no words. It directly states what the tool does without redundant elaboration.
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 tool's simplicity (no params, no output schema), the description is minimally sufficient, but it does not elaborate on what 'information' is returned (e.g., name, email, ID). This lack of detail could leave an agent uncertain about the response structure.
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 description does not need to explain any. Per the rubric, zero parameters receive a baseline of 4 since there is no schema to compensate for.
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 'Get' and clearly identifies the resource as 'current authenticated user information'. It unambiguously distinguishes itself from sibling tools (e.g., get_oauth_url, list_events) 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies this is for retrieving the currently authenticated user's profile. While it does not explicitly mention when not to use it or name alternatives, the context is clear and no exclusions are needed given the tool's simplicity.
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:

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

Score Badge

Copy to your README.md:

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

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/meAmitPatil/calendly-mcp-server'

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