list_team_membersList the members of a team, each with role flags (isLead, isOrgAdmin) and the underlying user (preferredName, email). Parabol GraphQL: viewer.team(teamId).teamMembers. Requires TEAMS_READ.
| Name | Required | Description | Default |
|---|---|---|---|
| sortBy | No | Optional field to sort members by (e.g. 'preferredName'). | |
| teamId | Yes | The team id. |
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 declare readOnlyHint=true, and the description adds the required TEAMS_READ permission, which helps agents anticipate authorization failures. It also discloses the exact response shape. It does not discuss pagination or sort behavior, but for a read-only list tool the added context is sufficient.
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 compact and front-loaded: it states the purpose, output fields, underlying query, and required permission in two sentences. Every sentence adds value, and there is no redundant information.
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?
Despite having no output schema, the description explicitly lists the returned fields (role flags, preferredName, email) and the required authorization. It is complete for a simple read-only list operation, though it omits details like default sort order or error handling, which are minor given the schema coverage.
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 both 'teamId' and 'sortBy'. The description does not add new parameter semantics beyond restating that the teamId is used and that members are sorted by the optional field, so a 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 states a specific verb ('List'), a specific resource ('the members of a team'), and the exact data shape returned (role flags, underlying user fields). It also provides the underlying GraphQL query, which distinguishes it from siblings like 'list_teams' or 'list_organization_users' by making the resource scope unambiguous.
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 clearly implies when to use this tool—when you need team membership with role and user details. It provides contextual clues like the required permission and GraphQL query, but it does not explicitly mention alternatives or state when not to use it, so it stops 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.
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.