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jhanglim

Mattermost MCP Server

by jhanglim

get_teams

Retrieve all teams the current user belongs to in Mattermost for team management and access control.

Instructions

현재 사용자가 속한 모든 팀 목록을 가져옵니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The main MCP tool handler for 'get_teams' in the CallToolRequestSchema switch statement. It calls client.getTeams() and returns the result as JSON text.
    case "get_teams": {
      const teams = await client.getTeams();
      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(teams, null, 2),
          },
        ],
      };
    }
  • The MattermostClient method that fetches the current user's teams via the Mattermost API endpoint /users/me/teams. This is the core implementation logic invoked by the tool handler.
    async getTeams() {
      return await this.request("/users/me/teams");
    }
  • src/index.ts:257-264 (registration)
    Registration of the 'get_teams' tool in the listTools response, including name, description, and empty input schema.
    {
      name: "get_teams",
      description: "현재 사용자가 속한 모든 팀 목록을 가져옵니다.",
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
  • Input schema definition for the 'get_teams' tool, which requires no parameters.
      inputSchema: {
        type: "object",
        properties: {},
      },
    },
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does but doesn't describe important behavioral aspects: whether this requires authentication, what format the team list returns (just names or full objects), whether it's paginated, if there are rate limits, or what happens when the user belongs to no teams. For a read operation with zero annotation coverage, this is insufficient.

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 a single, efficient sentence that states exactly what the tool does with zero wasted words. It's appropriately sized for a simple tool and front-loads the core functionality.

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 has no annotations, no output schema, and the description provides only basic functionality without behavioral context, this is incomplete. For a tool that fetches user data, the description should address authentication requirements, return format, error conditions, or limitations. The current description is too minimal for effective agent use.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so the schema already fully documents the lack of parameters. The description appropriately doesn't discuss parameters since none exist. It gets a baseline 4 for zero-parameter tools that don't need parameter explanation.

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

Purpose4/5

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

The description clearly states the verb ('가져옵니다' - fetches/gets) and resource ('팀 목록' - team list) with scope ('현재 사용자가 속한' - that the current user belongs to). It distinguishes from siblings by focusing on teams rather than channels, messages, or users. However, it doesn't explicitly differentiate from potential similar team-related tools that might exist.

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. It doesn't mention when this tool is appropriate versus searching for teams, getting team details, or using other sibling tools. There's no context about prerequisites, limitations, or alternatives.

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

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