Mode Manager MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| create_instructionA | Create a new VS Code .instructions.md file with the specified description and content. |
| list_instructionsA | List all VS Code .instructions.md files in the prompts directory. |
| get_instructionA | Get the raw content of a VS Code .instructions.md file. |
| update_instructionA | Update an existing VS Code .instructions.md file with new description or content. |
| delete_instructionA | Delete a VS Code .instructions.md file from the prompts directory. |
| optimize_memoryB | Manually optimize a memory file using AI to reorganize and consolidate entries while preserving all information. |
| memory_statsC | Get detailed statistics and optimization status for a memory file. |
| configure_memory_optimizationC | Configure memory optimization settings for auto-optimization behavior. |
| rememberA | Store user information persistently for future conversations. When users share preferences, coding standards, project details, or any context they want remembered, use this tool. Extract the key information from natural language and store it appropriately. The system automatically detects scope (user/workspace) and language specificity from context. For ambiguous cases, you will receive clarification prompts to ask the user. Examples of what to remember: coding preferences ('I like detailed docstrings'), project specifics ('This app uses PostgreSQL'), language standards ('For Python, use type hints'), workflow preferences ('Always run tests before committing'). Use only the memory_item parameter with natural language - the system handles scope detection. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| onboarding | Direct onboarding instructions for Copilot, including memory file structure. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 9 tools
Each tool targets a specific action: memory optimization settings, instruction CRUD, storage, and statistics. There is no overlap; 'remember' and 'optimize_memory' are clearly distinct.
Most tools follow verb_noun pattern (e.g., create_instruction, list_instructions), but 'memory_stats' is noun_noun and 'remember' is a single verb, breaking consistency.
9 tools cover two domains (5 for instructions, 4 for memory optimization) without being excessive or insufficient for the stated purpose.
Instruction management has full CRUD, but memory management lacks tools to list, get, or delete stored memories, leaving noticeable gaps in the workflow.