Gives Claude persistent memory through semantic search over stored text snippets. Exposes seven tools: memory_store for saving content with optional namespaces and tags, memory_search for cosine similarity lookups, plus get, delete, list, update, and stats operations. Supports three embedding backends out of the box: TF-IDF with no dependencies, OpenAI's text-embedding-3-small, or local Ollama models. Reach for this when you need Claude to remember user preferences, project context, or domain knowledge across conversations. Stores everything in a local database that persists between sessions. Install via pip, configure the embedding backend through environment variables, and start storing queryable memories immediately.
An MCP server that gives LLMs persistent, searchable semantic memory.
pip install mcp-external-memory
from mcp_external_memory import memory_store, memory_search
# Store a memory
result = memory_store(content="Alice prefers dark mode", namespace="users", tags=["alice", "ui"])
# Search memories
results = memory_search(query="what does Alice prefer?", namespace="users")
mcp-external-memory --help
| Tool | Description |
|---|---|
memory_store | Persist text + optional namespace/tags/metadata |
memory_search | Semantic search (cosine similarity) over all memories |
memory_get | Retrieve a single memory by ID |
memory_delete | Delete a memory by ID |
memory_list | List memories with optional namespace/tag filter + pagination |
memory_stats | Count of memories, namespaces, DB path |
memory_update | Update an existing memory |
The server supports multiple embedding backends:
text-embedding-3-small modelSet via MEMORY_EMBED_BACKEND environment variable.
git clone https://github.com/daedalus/mcp-external-memory.git
cd mcp-external-memory
pip install -e ".[test]"
# run tests
pytest
# format
ruff format src/ tests/
# lint
ruff check src/ tests/
# type check
mypy src/
mcp-name: io.github.daedalus/mcp-external-memory
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