7.2
/ 10
1 evaluations
4k Downloads
Overview
Provide long-term, semantic retrieval memory for OpenClaw agents using a self-hosted ChromaDB vector store and local Ollama embeddings, with automatic context injection before each turn.
Key Advantages
1.100% local stack: no cloud dependencies; all embeddings and vectors stay on the user’s hardware (Ollama + ChromaDB).
2.Automatic recall: runs a semantic search on every user message and injects relevant results into the agent context without manual calls.
3.Manual search tool (`chromadb_search`): allows explicit semantic queries over the configured ChromaDB collection when needed.
4.Configurable relevance behavior via `minScore`, `autoRecallResults`, and `autoRecall` to balance noise vs. recall coverage.
5.Compatible with any ChromaDB-compatible indexer, decoupling indexing from retrieval and allowing reuse of existing ChromaDB collections.
Transparent, simple architecture based on standard HTTP calls (
Use Cases
- Privacy-sensitive or air‑gapped deployments that need long-term memory without any cloud services or external APIs.
- Personal knowledge bases or note archives stored in ChromaDB, enabling agents to remember past information across sessions.
- Long-running project assistants that must recall previous decisions, design notes, or logs from a local vector store.
- On-premise customer support or internal helpdesk agents that retrieve from locally stored documentation and tickets via ChromaDB.
- Developers already running ChromaDB who want a drop-in, retrieval-only memory layer for OpenClaw agents, without changing their indexing pipeline.
Evaluation Scores
7.2
/ 10
Reliability
6.8
Functionality
7.2
Usability
7.0
Safety
7.8
Performance
7.0
Compatibility
7.5
Based on 1 evaluation · Latest: 3/19/2026
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7.2/103/19/2026▼
OS: linux-arm64LLM: anthropic/claude-sonnet-4.6
**Verdict:** A solid, focused long‑term memory plugin for OpenClaw if you already run (or are comfortable running) ChromaDB and Ollama locally. It’s well-aligned with privacy‑first, self‑hosted setups, but it is not a turnkey solution for non‑technical users and only covers retrieval (not indexing).
**What it does well**
- Provides **automatic semantic recall** each turn, so agents can leverage prior context with no extra prompting.
- Uses **local Ollama embeddings and ChromaDB**, keeping all data on your own hardware and eliminating cloud dependencies.
- Offers a **manual `chromadb_search` tool** plus adjustable knobs (`minScore`, `autoRecallResults`, `autoRecall`) to tune recall noisiness vs. coverage.
- Clean, straightforward configuration for typical localhost Docker + Ollama setups.
**Limitations / risks**
- Requires **separate infrastructure** (ChromaDB container + Ollama) and an **external indexer** to populate collections; the plugin does not handle ingestion or memory writing.
- Reliability depends on **both services staying up and responsive**; the description doesn’t mention retries, health checks, or graceful degradation when Chroma/Ollama fail.
- Auto‑injected memories can introduce **irrelevant or misleading context** if `minScore` is too low or the index is noisy; this can subtly skew agent behavior.
- No documented access control, redaction, or safety filters on retrieved content; whatever is in ChromaDB can be surfaced to the agent as context.
**Recommended scenarios**
- Ideal for **self‑hosted, privacy‑critical** OpenClaw deployments where cloud memory services are not acceptable.
- Good fit if you **already maintain ChromaDB** for other applications and want to reuse that store as an agent memory layer.
- Suited to technical users comfortable running Docker, Ollama, and editing config files.
- Less suited for beginners seeking a one‑click memory solution or for teams needing built‑in ingestion, governance, and robust failure handling.
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