Skip to main content
Glama

list_teams

Retrieve a paginated list of all teams from the Fathom AI meeting intelligence platform. Use page and page_size parameters to navigate through results.

Instructions

List all teams.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (starts at 1). Any page can be requested directly.
page_sizeNoNumber of teams per page (default 10).

Implementation Reference

  • The tool handler for 'list_teams' that fetches teams from the Fathom client and caches the result.
    async args => {
      const client = getClient();
      const key = cacheKey('list_teams', {});
    
      let cached = _itemsCache.get(key);
      const isExpired = cached !== undefined && Date.now() - cached.fetchedAt > CACHE_TTL_MS;
      if (!cached || isExpired) {
        try {
          const result = await fetchAll(opts =>
            client.listTeams((opts as Record<string, unknown>).cursor as string | null)
          );
          const entry = { ...result, fetchedAt: Date.now() };
          _itemsCache.set(key, entry);
          cached = entry;
        } catch (err) {
          const msg = err instanceof Error ? err.message : String(err);
          return { content: [{ type: 'text', text: `Error fetching teams: ${msg}` }] };
        }
      }
    
      const [pageItems, totalPages] = getPage(cached.items, args.page, args.page_size);
    
      if (pageItems.length === 0) {
        return {
          content: [{ type: 'text', text: `No teams found (page ${args.page} of ${totalPages}).` }],
        };
  • src/server.ts:484-502 (registration)
    Tool registration for 'list_teams' in the server.
    server.registerTool(
      'list_teams',
      {
        description: 'List all teams.',
        inputSchema: {
          page: z
            .number()
            .int()
            .min(1)
            .default(1)
            .describe('Page number (starts at 1). Any page can be requested directly.'),
          page_size: z
            .number()
            .int()
            .min(1)
            .default(DEFAULT_PAGE_SIZE)
            .describe('Number of teams per page (default 10).'),
        },
      },
  • The low-level API call implementation for listTeams.
    async listTeams(cursor?: string | null): Promise<Record<string, unknown>> {
      return this._get('/teams', { cursor });
    }
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List all teams' implies a read-only operation, but it doesn't mention pagination behavior, rate limits, authentication needs, or what 'all' entails (e.g., if it includes archived teams). For a tool with no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence, 'List all teams.', which is front-loaded and wastes no words. It efficiently conveys the core purpose without unnecessary elaboration, making it easy to parse and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (a list operation with pagination), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return format, pagination details, or any constraints, leaving the agent with insufficient context to use the tool effectively. The schema covers parameters well, but overall completeness is poor due to missing behavioral and output information.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% description coverage, with clear documentation for 'page' and 'page_size' parameters. The description adds no additional meaning beyond the schema, as it doesn't mention pagination or parameter usage. Given the high schema coverage, the baseline score of 3 is appropriate, as the schema adequately handles parameter semantics without description input.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'List all teams' clearly states the verb ('List') and resource ('teams'), making the purpose understandable. However, it lacks specificity about scope or differentiation from sibling tools like 'list_team_members' or 'list_meetings', which could cause confusion about what exactly is being listed. It's adequate but vague.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With sibling tools like 'list_team_members' and 'list_meetings', there's no indication of when to choose 'list_teams' over these, nor any context about prerequisites or typical use cases. This absence of guidance could lead to incorrect tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/jerichosequitin/fathom-ai-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server