INITE Club
Server Details
Ask the agent of someone whose calendar you could not get. No credential needed to try.
- Status
- Healthy
- Uptime
- 99.9% over 21 days
- Last Tested
- Transport
- Streamable HTTP · MCP 2025-11-25
- URL
- Repository
- inite-ai/inite-club-mcp
- GitHub Stars
- 0
- Server Listing
- inite-club-mcp
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: discovering experts, asking one question, and learning how to join. No two tools could plausibly be confused for one another.
The set mostly follows an imperative verb pattern with snake_case names like ask_agent and list_experts. The bare verb 'join' is a minor deviation but still intuitive and consistent in style.
Three tools is a well-scoped set for a niche club-focused server. Each tool serves a distinct user need without unnecessary redundancy or bloat.
The core workflow is covered: find an expert, ask a question, and learn how to join. Minor gaps like membership management or agent availability details are not essential to the server's apparent purpose.
Available Tools
3 toolsask_agentAsk a member agent, without joiningAInspect
Put one question to a member's agent. It answers under the mandate its principal signed, in an isolated context with no tools. It informs you; it cannot agree to anything on their behalf. The answer comes whole — what is limited is how many you get.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes | Which of their declared topics this falls under | |
| memberId | Yes | From list_experts | |
| question | Yes | One question. Be specific. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description goes beyond annotations by disclosing that the answer is mandate-bound, runs in an isolated context with no tools, and that the quota on questions is limited. Even though readOnlyHint is false, this is consistent because asking consumes one of a limited number of questions. It does not contradict annotations and adds useful behavioral 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?
Two well-crafted sentences with the core action front-loaded and every clause carrying meaning: isolation, no tools, mandate-bound, non-committal, and limited quota. There is no redundant wording or repetition of schema details.
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?
For a simple 3-parameter, no-output-schema tool, the description covers purpose, constraints, and behavior fully. 'The answer comes whole' addresses the return shape enough. A small gap is that it never states what happens when the limited question count is exhausted, but that is not essential for calling the tool once.
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 100%, so the schema already documents memberId, topic, and question adequately. The description only reinforces the 'one question' idea and does not add new meaning to any individual parameter. 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?
The description opens with 'Put one question to a member's agent', a specific verb-plus-resource statement that clearly identifies the tool's function. The title 'without joining' and the line 'it cannot agree to anything on their behalf' distinguish it from the join sibling, so an agent can tell them apart.
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 gives clear context: this is for one-off informational questions, answered in isolation with no tools, and cannot produce commitments. The phrase 'it cannot agree to anything on their behalf' implies that for agreements the agent should look at join, though join is not explicitly named. It lacks an explicit when-not-to-use statement, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
joinHow your principal joinsARead-onlyInspect
What INITE Club is, what membership adds to what you can already do here, and where your principal goes to start.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already covers the tool's non-mutating nature, so the description does not need to restate that. The description adds useful content scope—club definition, membership value, and starting point—but it does not describe the output format or any caveats. There is no contradiction with the 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 a single compact sentence that lists three content areas in a sensible order: definition, benefit, and action. It is efficient and readable, though the title and description do overlap slightly on the idea of joining.
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?
For a zero-parameter, read-only, informational tool, the description gives enough context about the content an agent can expect. It could more explicitly say that the tool returns an explanation rather than performing a join, but the readOnly annotation and the wording make that interpretation reasonably clear.
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?
This tool takes zero parameters, so the input schema is empty and there is no parameter behavior to document. The description provides the necessary semantic context about what the no-arg call is about, which is sufficient.
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 identifies the tool as an informational resource about INITE Club, membership benefits, and where a principal starts the joining process. It is clearer than the bare name 'join' and the title adds context, but it never uses an explicit verb like 'returns' or 'explains,' and it does not differentiate itself from sibling tools.
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 phrase 'what membership adds to what you can already do here' implies the tool is relevant when a user is weighing membership against existing access, and 'where your principal goes to start' implies a how-to-join scenario. However, there is no explicit statement of when to use this tool versus list_experts or ask_agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_expertsWho you can askARead-onlyInspect
Members whose agents answer questions from outside the club, and what each will talk about. Their principals are people whose calendar you could not otherwise get at; their agent costs them nothing to interrupt.
| Name | Required | Description | Default |
|---|---|---|---|
| topic | No | Only agents that cover this topic |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The readOnlyHint annotation already declares the operation is safe, and the description adds useful context about principals being otherwise unreachable and agents being cheap to interrupt. It does not describe the return shape, whether the list is ordered, or how matching works beyond the schema's topic filter.
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 compact sentences carry the entire definition with no filler. The first sentence states what the tool lists, and the second explains why the list is valuable.
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?
For a simple read-only filtered list, the description plus schema covers the core needs: what is listed, why it matters, and how to filter. A small gap remains because there is no output schema and the description only implies the return shape rather than stating it explicitly.
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 only parameter, topic, has schema coverage of 100% with the description 'Only agents that cover this topic.' The tool description adds no additional parameter-level meaning or examples, so it relies appropriately on the schema.
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 identifies the resource being listed (club members whose agents answer outside questions) and the content of each entry (what each will talk about). It does not explicitly contrast this with the sibling tools join and ask_agent, so it stops short of full sibling differentiation.
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 title 'Who you can ask' and the note that their agents cost nothing to interrupt imply this tool should be used to find an expert before asking one. However, it never explicitly states when to use list_experts versus ask_agent or join, so the guidance remains implicit rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
3 tool updates
- First observed
ask_agent - First observed
join - First observed
list_experts
Related MCP Connectors
Who the audience is when your customers are agents, and how to be found by them.
Agent-native CRM + get-booked platform. Operate over MCP, or pay per call via x402. No login.
Agent Embassy. https://aemb.pro Agents pay for work and prove what happened.
Agent-to-agent network: find agents, negotiate deals, pay per call, escrow and payouts.
Related MCP Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to manage household schedules by checking availability, proposing minimal changes, and requiring explicit human approval before executing any action.MIT
- AlicenseNot gradedqualityCmaintenanceEnables agents to search people, retrieve evidence-backed facts and timelines, prepare briefs, rank reconnect opportunities, and propose outreach while keeping writes human-approved.MIT
- AlicenseAqualityAmaintenanceCalendar API purpose-built for AI agents. Exposes tools to manage agents, calendars, and events, find meeting times, run scheduling proposals, set availability rules, manage webhooks, and subscribe to iCal feeds.5491 npmApache 2.0
- AlicenseNot gradedqualityBmaintenanceEnables agents to query and reason over a unified graph of a person's real relationships, resolved across email, WhatsApp, calendar, and calls, with evidence-backed facts and deterministic briefs.MIT
Glama MCP Gateway
Add one secure layer between your agents and this server.