WhenMeet.me
Server Details
Group meeting scheduler: Rank everyone’s available times across Google and Outlook, book Meet or Teams meetings between different organizations.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.1/5 across 8 of 8 tools scored.
Each tool targets a distinct operation—creation, slot finding, manual availability management, meeting details, and suggestion handling. No two tools have overlapping purposes.
All tool names follow a consistent verb_noun pattern in snake_case (e.g., create_meeting, find_common_slots, set_manual_availability), making them predictable and easy to differentiate.
With 8 tools, the server covers essential scheduling functionalities (create, find slots, manage availability, handle suggestions) without unnecessary bloat. This count is well-suited for the domain.
Core workflows are well-covered: finding slots, creating meetings, suggesting/responding to alternate times. Minor gaps exist, such as no direct meeting update or cancellation, but these are not critical for typical agent usage.
Available Tools
8 toolscreate_meetingAInspect
Confirm a meeting: writes the event into the authenticated host’s calendar with an optional Google Meet/Teams link, emails invites with an ICS attachment, and returns the share URL (/m/). Requires authentication.
| Name | Required | Description | Default |
|---|---|---|---|
| tz | No | IANA zone used to format times in invite emails. | |
| title | No | ||
| endsAt | Yes | unix ms | |
| startsAt | Yes | unix ms | |
| conference | No | Omit for no conference link. | |
| participants | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Describes core actions (write to calendar, email, return URL) but lacks details on side effects, error handling, or rate limits. Annotations only provide readOnlyHint=false, so description adds some value but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence conveying all essential actions and output. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main functionality and output, but could include guidance on when to use versus siblings and return format details. Still adequate for a mutation tool with moderate complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67%, and description does not add parameter-specific info beyond the schema. For undocumented parameters like 'title', no additional clarity is provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it confirms a meeting by writing to calendar, adding conference link, emailing invites, and returning share URL. Distinguishes itself from sibling tools like find_common_slots or suggest_time.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Indicates it is for confirming a meeting and requires authentication. Lacks explicit when-to-use vs alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_common_slotsARead-onlyInspect
Rank the best meeting times for the given participants, merging live Google/Microsoft calendar data, hand-marked availability and the heat-map sources. Each participant is filtered (Mon–Fri, waking hours) and scored in their OWN timezone; scores factor in buffer time around existing meetings and prefer sooner slots. Returns up to 8 slots: everyone-free slots first (allFree:true), then — only if there are too few — the best compromise slots (allFree:false) with a freeCount. Defaults to the next 14 days. Requires authentication.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | Window end, unix ms. Default: now + 14 days. | |
| tz | No | Requester IANA zone, e.g. Europe/Warsaw — the fallback zone for participants whose own timezone is unknown, and the zone for the round-hour scoring bonus. | |
| from | No | Window start, unix ms. Default: now. | |
| durationMin | No | Meeting length. Default 30. | |
| participants | Yes | Participant emails (the authenticated user is the host and should be included). |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behaviors beyond the readOnlyHint annotation: merging calendars, hand-marked and heat-map sources, filtering Mon-Fri waking hours, per-timezone scoring, buffer time, preference for sooner slots, and return structure (max 8 slots, allFree then compromise). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficient with about four sentences, front-loading the purpose. Every sentence adds value, though slightly more structure (e.g., bullet points) could improve scannability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (5 params, no output schema), the description covers algorithm, filters, scoring, and return format adequately. Missing error handling or exact output schema details, but sufficient for agent understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but the description adds meaning by explaining the role of tz (fallback zone and scoring bonus), that participants include the host, and the default values for from/to and durationMin.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Rank the best meeting times for the given participants,' which is a specific verb and resource. It distinguishes from siblings like suggest_time and get_meeting_availability by mentioning merging multiple data sources and scoring logic.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides context such as default window and authentication requirement, but does not explicitly state when to use this tool versus alternatives like suggest_time or get_meeting_availability. Usage is implied but not guided with exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_manual_availabilityARead-onlyInspect
Read previously hand-marked free slots for an email within a window.
| Name | Required | Description | Default |
|---|---|---|---|
| to | Yes | ||
| from | Yes | ||
| Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, and description confirms it's a read operation. It adds context about 'hand-marked' slots and 'within a window', but lacks details on authorization needs, empty results, or rate limits. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no fluff. Perfectly sized for the tool's simplicity (3 parameters, straightforward purpose).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, so description should hint at return format (e.g., list of time slots). It doesn't. However, tool complexity is low and annotations cover read safety, making it marginally adequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description must compensate. It indicates 'email' and a 'window' (from/to), but does not specify that 'from' and 'to' are Unix timestamps or provide format/units. This leaves ambiguity for an AI agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it reads hand-marked free slots for an email within a window. Verb 'Read' and resource 'previously hand-marked free slots' are specific, and it distinguishes from siblings like 'set_manual_availability' and 'get_meeting_availability'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description implies usage after manual availability has been set, but does not explicitly state when to use this tool vs alternatives like 'get_meeting_availability' or 'find_common_slots'. No exclusion criteria provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_meetingARead-onlyInspect
Read a meeting by its share-link id (the UUID from /m/): time, title, conference URL, host, and any proposed alternate times with their status.
| Name | Required | Description | Default |
|---|---|---|---|
| meetingId | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate readOnlyHint=true, and the description confirms a read operation. It adds transparency by detailing the response content (time, title, etc.), going beyond the annotation. The description is consistent and provides additional context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the purpose and includes all necessary details without extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema), the description covers input format and output fields sufficiently. It does not mention error handling or access permissions, but these are minor for a read operation. The sibling list provides broader context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for 'meetingId', but the description compensates fully by explaining that it is the UUID from the share-link URL (/m/<id>). This adds significant meaning beyond the raw schema definition.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states it reads a meeting by its share-link id, listing specific fields returned (time, title, conference URL, host, alternate times). This is a clear verb+resource with a distinct identifier method, and it distinguishes from sibling tools which handle creation, availability search, and suggestions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when you have a share-link id) and by listing sibling tools, the agent can infer alternatives. However, it does not explicitly state when not to use it or provide exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_meeting_availabilityARead-onlyInspect
Aggregated group availability for an existing meeting (the symmetric heat-map): per-30-min-slot counts of how many participants are free, plus ranked slots (per-participant timezones, buffer + soonness scoring, allFree:true everyone-free slots and allFree:false compromise slots). Individual calendars are never exposed. No auth needed — the meeting id is the capability.
| Name | Required | Description | Default |
|---|---|---|---|
| to | No | unix ms. Default: now + 14 days. | |
| tz | No | ||
| from | No | unix ms. Default: now. | |
| meetingId | Yes | ||
| durationMin | No |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations state readOnlyHint=true, and the description adds valuable behavioral context: 'Individual calendars are never exposed' and 'No auth needed — the meeting id is the capability.' This goes beyond annotations to explain privacy and access requirements.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (two sentences) and front-loads the core purpose. Every part adds value, with no extraneous words. However, some technical details (like the output structure) are packed densely, which could be clearer.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description explains the output structure well (counts, ranked slots, allFree) and notes auth requirements. However, given no output schema and 5 parameters, it lacks details on how parameters like 'tz' or 'durationMin' affect results, leaving gaps for an agent to apply the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 40% (2 of 5 parameters described). The description only implicitly references 'meetingId' (as 'existing meeting') and does not explain 'to', 'from', 'tz', or 'durationMin'. With low coverage, the description fails to compensate, leaving significant parameter ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns 'aggregated group availability' for an existing meeting, specifying the output format (per-30-min-slot counts, ranked slots, allFree slots). It distinguishes from siblings like 'find_common_slots' and 'get_manual_availability' by emphasizing aggregation and privacy (individual calendars not exposed).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does 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. The description mentions 'No auth needed' as a usage note, but fails to differentiate use cases from sibling tools like 'find_common_slots' or 'suggest_time'. Usage is implied but not clarified.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
respond_to_suggestionAInspect
Accept or decline a proposed alternate time. Accepting moves the meeting (calendar event included) and re-sends invites. Only the meeting host may call this — requires authentication.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | ||
| meetingId | Yes | ||
| suggestionId | Yes |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that accepting moves the meeting, includes calendar event, re-sends invites, and requires host authentication. Adds value beyond the readOnlyHint annotation (which is false, consistent).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Front-loads the core action and provides essential behavioral detail efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fairly complete for a mutation tool with 3 params and no output schema. Covers purpose, behavior, and auth. Could mention what happens on decline (likely no action), but not essential.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (no parameter descriptions in schema). The description does not detail the parameters (meetingId, suggestionId, action) or their formats. Only implies usage through context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the verb 'accept or decline' and the resource 'proposed alternate time'. Distinguishes from siblings like suggest_time (which proposes) and create_meeting (which creates).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: when there is a proposed alternate time, and who can call (only host, requires auth). Lacks explicit when-not-to-use or alternatives, but the context is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
set_manual_availabilityAInspect
Publish hand-marked FREE time slots for an email address (the no-calendar fallback, e.g. Apple iCloud users). Replaces previously marked slots inside the window; the group heat-map updates immediately. Authenticated callers (Bearer PAT) skip the bot challenge; an anonymous caller must pass a Cloudflare Turnstile token in turnstileToken (only required when the server is configured with a Turnstile secret).
| Name | Required | Description | Default |
|---|---|---|---|
| Yes | |||
| windowTo | Yes | unix ms | |
| freeSlots | Yes | ||
| windowFrom | Yes | unix ms | |
| turnstileToken | No | Cloudflare Turnstile token; required for anonymous callers when a Turnstile secret is configured. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond the readOnlyHint annotation by detailing that previously marked slots are replaced, the group heat-map updates immediately, and authentication requirements (Bearer PAT skip bot challenge, Turnstile token for anonymous callers). No contradictions found.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three sentences covering purpose, behavior, and authentication. Every sentence adds value with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers purpose, replacement behavior, update effects, and authentication. It lacks error conditions or rate limits but given the complexity (5 params, no output schema), the information is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the email parameter as the target for publishing slots and clarifies the turnstileToken requirement. With 60% schema coverage, it compensates by explaining the purpose of freeSlots as 'FREE time slots' and 'hand-marked', though schema already defines the structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool publishes hand-marked FREE time slots for an email address, specifying it as a no-calendar fallback. It distinguishes from siblings like get_manual_availability by indicating it sets availability rather than retrieving it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates this tool is a 'no-calendar fallback' for users like Apple iCloud users, providing context on when to use it. However, it does not explicitly state when not to use it or name alternative tools for calendar users.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
suggest_timeAInspect
Propose a different time for an existing meeting on behalf of a guest. The host is notified by email and can accept or decline. Authenticated callers (Bearer PAT) skip the bot challenge; an anonymous caller must pass a Cloudflare Turnstile token in turnstileToken (only required when the server is configured with a Turnstile secret).
| Name | Required | Description | Default |
|---|---|---|---|
| endsAt | Yes | unix ms | |
| message | No | ||
| startsAt | Yes | unix ms | |
| meetingId | Yes | ||
| suggestedBy | Yes | Email of the person proposing. | |
| turnstileToken | No | Cloudflare Turnstile token; required for anonymous callers when a Turnstile secret is configured. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, implying mutation. Description adds that the host is notified by email and can accept/decline, which is a behavioral trait beyond the annotation. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three front-loaded sentences: core purpose, notification behavior, authentication details. No redundant information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema, and description does not indicate what the tool returns (e.g., success status, suggestion ID). Lacks explanation of error cases or what happens if the host declines. Adequate but not fully complete for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 67% of parameters with descriptions (endsAt, startsAt, suggestedBy, turnstileToken). Description does not add new meaning to parameters beyond what schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action (propose a different time) and the target (existing meeting on behalf of a guest). This distinguishes it from sibling tools like respond_to_suggestion (which handles the host's response) and create_meeting (which creates a new meeting).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explains when to use (proposing a time for a guest) and provides authentication context (Bearer PAT vs. anonymous with Turnstile token). However, it does not explicitly mention when not to use or suggest alternative tools for other scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- AlicenseAqualityAmaintenanceGTM signal intelligence suite for AI agents. Six tools: hiring signals, tech stack detection, company-to-LinkedIn resolution, ICP scoring, job board scanning, and a combined signals aggregator. Built for outbound sales workflows.117371MIT

industrylens-mcpofficial
Flicense-qualityCmaintenanceBrowse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.
Sociality MCPofficial
Alicense-qualityDmaintenanceSocial media analytics, post insights, and competitor benchmarking for AI agents.6MIT- AlicenseAqualityAmaintenanceDetects hiring intent signals by scanning job boards for specific companies. Returns structured role data for outbound sales targeting.1761MIT