list_teamsList the teams the viewer belongs to, with each team's id, name, orgId, tier, and team lead. Parabol GraphQL: viewer.teams. Requires the TEAMS_READ scope.
| Name | Required | Description | Default |
|---|---|---|---|
| includeArchived | No | Include archived teams (default false). |
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 declare readOnlyHint, and the description adds useful behavioral context: it names the GraphQL source (viewer.teams), the required auth scope, and the exact fields returned. It stops short of describing pagination or response shape, but for this simple read operation the added context is strong.
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 front-load the core purpose and output fields, then add the data source and auth requirement. Every sentence earns its place with no redundant wording.
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 list operation with one optional parameter, the description fully covers purpose, output fields, data source, and required scope. No output schema exists, but the field list in the description compensates well.
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, includeArchived, is fully described in the schema with its default value, so schema coverage is 100%. The description adds no additional parameter-level meaning beyond what the schema already provides, placing it at the baseline score.
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?
States a clear verb and resource: lists the teams the viewer belongs to, with specific fields. The description precisely differentiates this from sibling tools like list_organizations or get_team.
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?
Clearly establishes context: this is for listing the current viewer's teams, with a TEAMS_READ scope prerequisite. It does not explicitly name alternatives or when not to use it, but the scope is specific enough for an agent to route correctly.
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.