Copilot Studio vs Plugin Engine
A side-by-side look at the Copilot Studio and Plugin Engine MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
C
Copilot StudioConversational AI · Local subprocess (stdio)MCP bridge for Copilot Studio sign-in, environment selection, and Agentic Builder access.59GoodAuth: oauth 2.0Verdict: choose Copilot Studio for conversational ai work as a local process; choose Plugin Engine for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
CChoose Copilot Studio when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: OAuth 2.0.
- You want tools like
discover_resources, get_consumption, manage_agents.
Choose Plugin Engine when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
COGNIGY_API_BASE_URL, COGNIGY_API_KEY. - You want tools like
create_ai_agent, update_ai_agent, setup_llm.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | C Copilot Studio | |
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 59/100 · Good | 61/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | OAuth 2.0 | API key required |
| Pricing | Not declared | BYOK (pay the provider) |
| Required env vars | None listed | COGNIGY_API_BASE_URLCOGNIGY_API_KEY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 3 | 18 |
| Directory activity | 0 views 0 installs 0 upvotes | 0 views 0 installs 0 upvotes |
| Tools | 5 | 18 |
| Full listing | View Copilot Studio | View Plugin Engine |
Tools & capabilities
Copilot Studio tools 5
discover_resourcesDiscover connector operations and schemas, existing connections, dependent parameter values, and attachable resources.get_consumptionRead historical agent or workflow credit consumption, or current environment credit capacity.manage_agentsManage agent inventory, complete draft authoring, lifecycle, published-agent sharing, saved-draft previews, and agent evaluation suites and runs.manage_workflowsManage workflow inventory, complete draft authoring, lifecycle, real tests, and run diagnostics.get_copilot_studio_skillsStart here for Copilot Studio guidance. Read the matching core skill before authoring, then read `schema.json`.
Plugin Engine tools 18
create_ai_agentCreate a complete AI Agent with auto-provisioned flow, job node, and REST endpointupdate_ai_agentUpdate persona, guardrails, job config (role, procedures, LLM, temperature)setup_llmCreate an LLM resource (GPT-4, Claude, Mistral, etc.) with automatic connection validationtalk_to_agentSend a message to an AI Agent and get its response (uses Endpoint Test Mode, so it is not counted as billable)list_resourcesList projects, agents, flows, endpoints, LLMs, knowledge stores, and moreget_resourceGet detailed information about a single resourcedelete_resourcePermanently delete a resourcemanage_knowledgeCreate knowledge stores, add sources (URL, text, file), list chunks for RAGcreate_toolAdd a tool (HTTP, knowledge, email, MCP, A2A) to an agent's job nodeupdate_toolUpdate an existing tool node's configurationmanage_webchatCreate or configure a Webchat v3 endpoint for website deploymentmanage_flow_nodesCreate, update, delete, or list flow nodes for conversation logic- +6 more on the listing page
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Copilot Studio
{
"mcpServers": {
"copilot-studio": {
"command": "npx",
"args": [
"-y",
"@microsoft/copilot-studio-mcp@latest"
]
}
}
}
Plugin Engine
{
"mcpServers": {
"cognigy-plugin-engine": {
"command": "npx",
"args": [
"-y",
"-p",
"@cognigy/plugin-engine@latest",
"cognigy-setup"
],
"env": {
"COGNIGY_API_BASE_URL": "YOUR_COGNIGY_API_BASE_URL_HERE",
"COGNIGY_API_KEY": "YOUR_COGNIGY_API_KEY_HERE"
}
}
}
}
Frequently asked questions
Copilot Studio is categorized under Conversational AI and uses a local stdio subprocess. Plugin Engine belongs to Conversational AI and uses a local stdio subprocess. Pick Copilot Studio for conversational ai work and Plugin Engine for conversational ai.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Copilot Studio has no declared pricing — check the project's own site. Auth: oauth 2.0. Plugin Engine is bring-your-own-key: usage is billed by the API provider you supply a key for. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add copilot-studio and cognigy-plugin-engine as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Copilot Studio has a quality signal of 59/100 (Good) with 0 views, 0 installs and 3 GitHub stars. Plugin Engine has 61/100 (Good) with 0 views, 0 installs and 18 GitHub stars.