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Copilot Studio MCP

Copilot Studio MCP

by jgt87
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
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List agents

cs_list_agents

List Copilot Studio agents in a Power Platform environment via Power Platform CLI or Dataverse to discover and manage available agents.

Instructions

List Copilot Studio agents in an environment. via 'pac' uses 'pac copilot list' (needs a pac auth profile); via 'dataverse' queries the bots table with the MSAL token. Default auto: pac when available, else dataverse.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "cs_list_agents"
  }
}

Input Schema

NameRequiredDescriptionDefault
viaNo
clientIdNoEntra app (client) id for MSAL. Defaults to CPS_CLIENT_ID, then the first-party VS Code id.
tenantIdNoEntra tenant id. Defaults to the workspace sync metadata, then CPS_TENANT_ID.
ownerOnlyNo
workspaceNoPath to (or inside) the agent workspace. Defaults to CPS_WORKSPACE or the current directory.
dataverseUrlNo
environmentIdNoPower Platform environment id (GUID). Defaults to workspace sync metadata or CPS_ENVIRONMENT_ID.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.8
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.5

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose non-obvious behavior: two distinct execution backends, the auth prerequisite for the pac path ('needs a pac auth profile'), the MSAL-token path for dataverse, and the auto-fallback rule. It omits read-only confirmation, failure behavior, and pagination/result-size traits, so it is informative but not complete.

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?

Three dense sentences, front-loaded with the purpose followed by mechanism and default resolution; every sentence carries information. The parenthetical backend notes are terse but readable, with no filler.

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

Completeness3/5

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

For a 7-parameter, zero-annotation tool with no output schema, the description covers the primary behavioral mode but says nothing about what is returned (fields, count, pagination) or how the unlisted parameters (ownerOnly, dataverseUrl) affect results. It is adequate to start a call but leaves the agent to discover output shape empirically.

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?

Schema coverage is only 57%, and the description meaningfully explains the single enum parameter ('via') by mapping each value to its backend behavior — value the schema's bare enum does not provide. It adds nothing for ownerOnly or dataverseUrl, which are undocumented in both the schema and the description, so it only partially compensates for the coverage gap.

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?

States a specific verb and resource ('List Copilot Studio agents in an environment') and even names the underlying mechanisms, so the core purpose is unambiguous. It does not, however, distinguish itself from the close sibling cs_list_org_agents, leaving the agent to guess which listing scope applies.

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

Usage Guidelines3/5

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

The description gives real decision logic for the 'via' modes (pac when available, else dataverse) and notes the pac auth-profile prerequisite. It stops short of when-to-use guidance against alternatives such as cs_list_org_agents or cs_env_list, so usage is only implied at the tool-selection level.

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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