Memory Tracker MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | Your OpenAI API key |
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| save_memoryD | – |
| search_memoryC | Search memories in the vector store and return relevant chunks |
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 2 tools
The two tools, save_memory and search_memory, have clearly distinct purposes: one writes a memory and the other reads/retrieves them. No overlap or ambiguity exists.
Both tool names follow a consistent verb_noun pattern (save_memory, search_memory), using the same resource noun. The naming is predictable and uniform.
With only two tools, the set is at the low end of what is reasonable. For a memory tracker, save and search are core operations, so the count is borderline but acceptable.
The server covers the primary create and read/search operations, but it lacks update, delete, or list-all functionality. These are significant gaps for a complete memory management lifecycle.