hippmem-mcp
Enables AI assistants to have persistent associative memory across sessions by storing memories, discovering associations, and retrieving them via spreading activation.
README
hippmem-mcp
MCP server for HIPPMEM — give AI tools long-term associative memory.
What is HIPPMEM?
HIPPMEM is a native associative memory engine for AI agents, written in Rust. Instead of storing text chunks and searching them by vector similarity, it discovers associations between memories at write time and retrieves them via spreading activation at read time — so the AI recalls not just what was said, but how things connect and why.
It runs fully offline with a deterministic fallback backend.
What is hippmem-mcp?
hippmem-mcp wraps HIPPMEM as a Model Context Protocol server. Configure it once in Claude Desktop (or any MCP-compatible tool), and your AI assistant gains persistent, associative memory across sessions — no API key required.
AI Tool (Claude Desktop / VS Code / ...)
│ MCP protocol (stdio)
▼
hippmem-mcp
│ Python bindings
▼
hippmem Engine (Rust)
│
▼
Local storage (redb + Tantivy + HNSW)
Key Features
- Zero config —
pip installthen one JSON block in your MCP client configuration; deterministic fallback backend works offline - Write-time association discovery — entities, topics, goals, causal links extracted and scored automatically
- Spreading activation retrieval — multi-channel seed recall (BM25 + entity + semantic + temporal + topic) fused by RRF
- Graph evolution — co-activated connections strengthen (Hebbian learning); stale edges decay
- Explanation traces — every result shows why it was recalled via
dimensionsandmatched_dimensions - Single-file storage — one redb file + Tantivy full-text index + HNSW vector index; no external database
Install
pip install hippmem-mcp
Requires Python ≥ 3.11.
Configure
Claude Desktop
Add to claude_desktop_config.json:
{
"mcpServers": {
"hippmem": {
"command": "python",
"args": ["-m", "hippmem_mcp.server"]
}
}
}
Or use the entry point:
{
"mcpServers": {
"hippmem": {
"command": "hippmem-mcp"
}
}
}
Environment Variables
Copy .env.example to .env and configure:
| Variable | Default | Description |
|---|---|---|
HIPPMEM_EMBEDDING_PROVIDER |
(empty = deterministic) | Embedding backend: openai-compatible or leave empty for offline fallback |
HIPPMEM_EMBEDDING_BASE_URL |
https://api.openai.com/v1 |
API endpoint when using remote embeddings |
HIPPMEM_EMBEDDING_MODEL |
text-embedding-3-small |
Model name for embeddings |
OPENAI_API_KEY |
(none) | API key for OpenAI-compatible embedding services |
The deterministic fallback backend requires no API key, no GPU, and no network connection.
Claude Code
Claude Code supports MCP natively. Add to your Claude Code MCP config (.claude/mcp.json or project .mcp.json):
{
"mcpServers": {
"hippmem": {
"command": "hippmem-mcp"
}
}
}
Then in any Claude Code session:
Use retrieve_memories to check what we know about this project before starting.
Other MCP Clients
hippmem-mcp speaks standard MCP over stdio. Configure any MCP-compatible client the same way — point the command to hippmem-mcp or python -m hippmem_mcp.server.
Tools
| Tool | Description |
|---|---|
write_memory |
Write a memory. The engine automatically discovers associations with existing memories. Supports content_type (Decision, Preference, ProjectKnowledge, TaskState, Correction, Event, Reflection) and importance (0.0–1.0). |
retrieve_memories |
Cross-session associative recall via multi-channel seed retrieval + spreading activation. Returns scored results with dimensions explaining why each memory was recalled. Supports top_k and max_hops tuning. |
Development
git clone https://github.com/hippmem/hippmem-mcp.git
cd hippmem-mcp
pip install -e ".[dev]"
pytest
See CONTRIBUTING.md for commit conventions, PR workflow, and DCO requirements.
Documentation
- Best Practices — when to write, how to query, prompt templates
- HIPPMEM main project — engine architecture, concepts, and API reference
- MCP specification — Model Context Protocol
- Changelog
- Security policy
License
Apache 2.0. See LICENSE and COPYRIGHT.
The underlying HIPPMEM engine (hippmem) is AGPL-3.0-only. A commercial license is available — contact hippmem@gmail.com.
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