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COR MCP Server

COR MCP Server

by fxckcode
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

cor_add_team_users

Add multiple users to a specific team using team ID and user IDs. Streamline team membership management.

Instructions

Add users to a team.

Args: team_id: The team ID user_ids: List of user IDs to add

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "team_id": "<team_id>",
      "user_ids": "<user_ids>"
    },
    "name": "cor_add_team_users"
  }
}

Input Schema

NameRequiredDescriptionDefault
team_idYes
user_idsYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It only states 'Add users to a team' without mentioning permissions, side effects, error handling (e.g., non-existent team), or idempotency. This is insufficient for an AI agent to understand the tool's full impact.

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

Conciseness4/5

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

The description is very concise (one sentence plus a parameter list) and front-loaded with the action. However, the 'Args:' section is redundant with the input schema, slightly reducing efficiency. Overall, it wastes no words.

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?

For a mutation tool, the description fails to address important aspects like return values (despite an output schema existing), error conditions, or whether adding duplicate users is handled. An AI agent would lack sufficient information for safe invocation.

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?

Although schema description coverage is 0%, the description adds minimal meaning by restating parameters as 'The team ID' and 'List of user IDs to add'. This clarifies the intent beyond the schema titles but lacks additional context like valid ranges or format requirements.

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

Purpose5/5

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

The description clearly states the tool's action as 'Add users to a team', specifying the verb (add) and resource (team users). This distinguishes it from siblings like cor_remove_team_users (removing users) and cor_create_team (creating a team), making the purpose unambiguous.

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 (e.g., cor_add_project_collaborator) or any prerequisites. It lacks context about typical workflows or exclusions, leaving the agent to infer usage from the name alone.

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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