memsprout
Server Details
shared AI-context layer for teams — persistent memory your agents search and update over MCP
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- Status
- Unhealthy
- Uptime
- 0.0% over 37 days
- OAuth
- Works in Glama
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- memsprout/agents
- GitHub Stars
- 0
TDQS
Scored across 21 tools
Most tools have clearly distinct purposes, with only two pairs of intentional duplicates (fetch/get_memory, search/search_memories) that create minor ambiguity. Descriptions explicitly state they are provided for host compatibility, but an agent might still select the wrong one.
The majority of tools follow a consistent verb_noun pattern. Two tools (fetch, search) use generic names that deviate from the pattern, and memsprout_onboarding uses a different naming style, but overall the naming is predictable and readable.
With 21 tools, the server covers a broad but focused domain of memory management. The count is slightly above the typical range but each tool serves a distinct purpose and earns its place, making it appropriate for the scope.
The tool surface is highly complete: full CRUD for memories, spaces, topics, and assets; multiple upload methods; search and list variants; onboarding and movement. No obvious gaps in core workflows.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
21 tool updates
- First observed
attach_asset - First observed
create_space - First observed
create_topic - First observed
delete_memory - First observed
delete_topic - First observed
detach_asset - First observed
fetch - First observed
get_asset - First observed
get_memory - First observed
get_signed_upload_url - First observed
get_upload_link - First observed
list_memories - First observed
list_spaces - First observed
list_topics - First observed
memsprout_onboarding - First observed
move_memory - First observed
search - First observed
search_memories - First observed
store_memory - First observed
update_memory - First observed
update_topic
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