get_teamFetch one team by id: metadata, its team members (with each member's user), active meetings, and organization. Parabol GraphQL: viewer.team(teamId). Requires TEAMS_READ (+ MEETINGS_READ for activeMeetings, ORGS_READ for organization).
| Name | Required | Description | Default |
|---|---|---|---|
| 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?
The readOnlyHint annotation already signals a safe read operation, and the description adds value beyond that by disclosing the exact GraphQL query path (viewer.team(teamId)) and the permission scopes required (TEAMS_READ, plus conditional MEETINGS_READ and ORGS_READ). It also exposes what data will be included in the result, which is helpful 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?
The description is compact: the first sentence communicates the core action and result content, and the second adds the essential GraphQL and permission context. It is front-loaded with the most important information and contains no filler or redundant restatement of the title.
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?
With a single well-documented parameter, readOnly annotation, and no output schema, the description carries the full responsibility for return-value context. It does so by explicitly listing the included sub-resources and the permission prerequisites, making it complete enough for an agent to select and invoke 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 only parameter, teamId, has full schema description coverage with 'The team id.' The description adds nothing semantically beyond the schema because it only refers to 'by id' without giving format, example, or source guidance. Baseline 3 is appropriate because the schema already documents the parameter adequately.
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 a specific verb and resource: 'Fetch one team by id'. It further defines the scope by enumerating the returned data (metadata, team members with each member's user, active meetings, and organization), which clearly distinguishes it from sibling tools like list_teams, get_meeting, and get_organization.
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 frames when to use this tool: when you need a single team and its related members, meetings, and organization. It does not explicitly name alternatives or exclusions, but the id-based singular scope and the embedded permission requirements provide clear contextual guidance.
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.