Copilot Studio Agent Direct Line MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DIRECT_LINE_SECRET | Yes | Direct Line secret key from your Copilot Studio Agent |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| send_messageC | Send a message to the Copilot Studio Agent |
| start_conversationB | Start a new conversation with the Copilot Studio Agent |
| end_conversationB | End an existing conversation and clean up resources |
| get_conversation_historyB | Retrieve message history for a conversation |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose with no overlap: start_conversation initiates, send_message communicates, get_conversation_history retrieves, and end_conversation terminates. The four tools cover the complete conversation lifecycle without any ambiguity.
All tool names follow a consistent verb_noun pattern (e.g., start_conversation, send_message) using snake_case throughout. The naming is predictable and readable, with no deviations in style or convention.
Four tools are well-scoped for a conversation management server, covering initiation, messaging, history retrieval, and termination. Each tool earns its place without being excessive or insufficient for the domain.
The tool set provides complete CRUD/lifecycle coverage for conversation management: start (create), send (update/communicate), get (read), and end (delete). There are no obvious gaps, and agents can handle the full workflow without dead ends.