start_checkinMUTATES Parabol data: start a new Check-in (Action) meeting for a team (returns the new meetingId). Required: teamId. Optionally name it. Parabol GraphQL: startCheckIn → union. Requires MEETINGS_WRITE.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Optional meeting name. | |
| teamId | Yes | The team id (required). |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already flag destructiveHint=true, and the description independently reinforces that this 'MUTATES Parabol data' while adding useful context: the required permission (MEETINGS_WRITE) and the return value (new meetingId). This goes beyond the annotation without contradicting it.
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 two sentences with no filler. The mutation warning is front-loaded, followed by essential inputs, permission, and return value, making every sentence earn its place.
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 two-parameter mutation tool with no output schema, the description is reasonably complete: it names the operation, parameters, permission requirement, and return value. It could be fuller about failure modes or union response details, but those are not critical for selecting and invoking this tool.
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% and both parameters already have descriptions. The description adds little beyond restating that teamId is required and name is optional, 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.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'start a new Check-in (Action) meeting for a team' and notes the returned meetingId. This cleanly distinguishes it from sibling tools like start_retrospective and start_team_prompt by naming the exact meeting type.
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 inputs ('Required: teamId. Optionally name it') and a mutation warning, but does not explicitly say when to choose this over the sibling start_* meeting tools. The use case is implied by the meeting type name rather than stated with alternatives or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Every tool targets a distinct resource and action: get_/list_ tools are clearly separate read paths, create_/update_/start_/add_ tools map to distinct mutations, and the two escape hatches are explicitly labeled. Even near neighbors like list_meetings and list_active_meetings are unambiguous.
Most tools follow a consistent pattern: list_/get_ for reads, create_/update_/start_ for mutations, with plural nouns for collections and singular for single resources. Minor deviations like add_comment, invite_to_team, and the parabol_* escape hatches prevent a perfect score.
With 21 tools, the server sits in the 16-25 range that feels heavy for an MCP surface. The breadth is somewhat justified because Parabol spans organizations, teams, meetings, tasks, and comments, but many tools are list/get variants of the same core entities.
Core read and write flows exist for teams, organizations, meetings, tasks, and comments, but there are notable lifecycle gaps such as no delete_task, no reflection update/delete, and no meeting end/update mutations. The parabol_graphql and parabol_query escape hatches help work around these gaps but do not make the curated surface fully complete.