mymemory-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
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| mymemory_get_contextA | Fetch the user's MyMemory vault context: a compiled context_block (directives first, then facts/preferences/notes, one per line) plus the raw active entries. Call once at conversation start and apply it — these are the user's standing rules, facts, and preferences across every AI tool they use. |
| mymemory_searchA | Search the user's MyMemory vault for a word or phrase. Case-insensitive substring match over active entries (text and kind). Returns { query, count, matches }. |
| mymemory_proposeA | Propose new entries to the user's MyMemory vault when you learn something durable about them. Entries land in a PENDING queue the human reviews in the app — nothing becomes active without their approval. Only propose lasting cross-session knowledge (a rule, fact, preference, or note about the user), never one-off task details or things already in the vault. kinds: directive = a rule ("never …", "always …"), fact, preference, note. Max 20 per call; the server dedupes against existing entries. |
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 3 tools
The three tools have distinct purposes: get_context (retrieve full vault), search (find specific entries), and propose (add new entries). While get_context and search both read data, their purposes are clearly separated (bulk fetch vs. targeted lookup), and propos e is clearly a write operation. No meaningful ambiguity between them.
All tool names follow a consistent mymemory_<verb> pattern: get_context, search, propose. The verbs are uniform and descriptive, and each name clearly signals its operation (retrieval, lookup, and write). The mymemory_ prefix consistently scopes the namespace.
Three tools is on the thin side but understandable for a personal memory vault: fetch, search, and write. The scope is narrow enough that three tools could work, though one might expect an explicit update/delete mechanism. It's at the lower boundary of reasonable.
The vault supports retrieval (get_context), search, and creation (propose, gated by PENDING approval). However, there's no tool to update or delete existing active entries, nor to approve the pending queue, meaning maintenance of the vault is delegated entirely to the human in the app. This leaves some lifecycle gaps beyond the core read/write flow.