Memory Cache MCP Server
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| store_dataC | Store data in the cache with optional TTL |
| retrieve_dataC | Retrieve data from the cache |
| clear_cacheC | Clear specific or all cache entries |
| get_cache_statsC | Get cache statistics |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Cache Statistics | Real-time cache performance metrics |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: clear_cache removes entries, get_cache_stats provides metrics, retrieve_data fetches data, and store_data saves data. There is no overlap or ambiguity between these four operations.
The naming is mixed: clear_cache and get_cache_stats follow a verb_noun pattern, but retrieve_data and store_data use a verb_object pattern. While readable, this inconsistency in structure (cache vs. data as the object) deviates from a uniform convention.
With 4 tools, this is well-scoped for a memory cache server. It covers the essential operations (store, retrieve, clear, stats) without being overly sparse or bloated, making each tool necessary and focused.
The toolset covers core cache operations: storing, retrieving, clearing, and monitoring. A minor gap is the lack of an update or delete specific entry tool, but agents can work around this by using clear_cache for deletion and store_data for updates, so it's mostly complete.