MCP Embedding Storage 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 |
|---|---|
| save-memoryC | Save content to vector database |
| search-memoryC | Search for information in vector database |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| save-memory | |
| search-memory |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have perfectly distinct purposes: one saves content to the vector database, while the other searches for information within it. There is no overlap or ambiguity between these operations, making it impossible for an agent to confuse them.
Both tools follow a consistent verb-noun pattern with hyphenated names (save-memory and search-memory). The verbs 'save' and 'search' clearly indicate the action, and 'memory' serves as a consistent noun, creating a predictable and readable naming convention throughout.
With only two tools, this server feels under-scoped for an embedding storage system. While save and search are core operations, typical vector database interfaces would include additional tools like delete, update, list, or manage collections, making the current set appear thin and incomplete for the domain.
The tool surface is severely incomplete for an embedding storage server. It lacks essential operations such as deleting or updating stored memories, listing available entries, managing collections or namespaces, and performing advanced searches (e.g., by metadata). This will likely cause agent failures when trying to perform full lifecycle management of stored data.