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zzlzzlzzl15

Memora - Personal Knowledge Base (RAG)

by Probieren · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ⚠ suspicious
118
Downloads
1
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0
Active Installs
2
Versions
Install in OpenClaw
/install memora-knowledge-base
Description
Memora — A self-hosted RAG (Retrieval-Augmented Generation) personal knowledge base. Built with FastAPI + Qdrant + DashScope/OpenAI Embedding + DeepSeek/Open...
Usage Guidance
This skill appears coherent and matches its description, but be mindful of two practical risks: (1) Uploads will read the local file path you provide and POST its contents to the server at KB_API_BASE — do not upload sensitive files unless you absolutely trust that backend. (2) KB_API_BASE can be any URL; if you set it to a remote/untrusted endpoint, the service will receive your queries, documents, and returned context. Prefer running the Memora backend locally (KB_API_BASE=http://127.0.0.1:8080) or on a trusted host, review the backend's source (SKILL.md links a GitHub repo) before connecting to unknown endpoints, and avoid giving the skill any credentials or backend URL that you wouldn't trust with your documents.
Capability Analysis
Type: OpenClaw Skill Name: memora-knowledge-base Version: 1.1.0 The skill provides functionality to read local files and upload them to a network endpoint, which are high-risk capabilities. While these actions are aligned with the stated purpose of a personal knowledge base (RAG), the script `scripts/kb_api.py` allows for arbitrary file access and data transmission to a configurable backend (`KB_API_BASE`). No evidence of intentional malice, obfuscation, or prompt injection was found, but the broad file and network access permissions warrant a suspicious classification per the provided analysis criteria for risky capabilities.
Capability Assessment
Purpose & Capability
Name/description (personal RAG knowledge base) aligns with the provided artifacts. The only required environment variable is KB_API_BASE (the backend URL) which is appropriate for a client that makes HTTP calls to a Memora backend. The included Python client (scripts/kb_api.py) performs search, upload, create, list, and detail operations that match the described features.
Instruction Scope
Runtime instructions tell the agent to run the included Python client with commands like upload/create/search. The client reads a file path when performing uploads and sends the file contents to KB_API_BASE: this is expected behavior for a document ingest feature, but it means the agent (or user prompts) can cause arbitrary local files to be read and transmitted to the configured backend. Ensure uploads are limited to intended files and that KB_API_BASE points to a trusted service.
Install Mechanism
There is no install spec (instruction-only skill) and only a small stdlib-only Python script is included. Nothing is downloaded at install time and no external packages are required by the client, which keeps install risk low.
Credentials
The skill only requires KB_API_BASE. This is proportional to a client that must know where the Memora backend lives. No unrelated secrets, tokens, or config paths are requested.
Persistence & Privilege
The skill does not request always:true, does not modify other skills, and does not require system-wide configuration changes. It can be invoked autonomously (platform default), which is expected for skills of this type.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install memora-knowledge-base
  3. After installation, invoke the skill by name or use /memora-knowledge-base
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
Rewrite SKILL.md: focus on RAG architecture, tech stack details (FastAPI + Qdrant + DashScope + DeepSeek), hybrid retrieval pipeline, English-first documentation.
v1.0.0
Initial release: semantic search, AI Q&A, document management (upload/create/list/detail), zero-dependency Python client.
Metadata
Slug memora-knowledge-base
Version 1.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Memora - Personal Knowledge Base (RAG)?

Memora — A self-hosted RAG (Retrieval-Augmented Generation) personal knowledge base. Built with FastAPI + Qdrant + DashScope/OpenAI Embedding + DeepSeek/Open... It is an AI Agent Skill for Claude Code / OpenClaw, with 118 downloads so far.

How do I install Memora - Personal Knowledge Base (RAG)?

Run "/install memora-knowledge-base" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Memora - Personal Knowledge Base (RAG) free?

Yes, Memora - Personal Knowledge Base (RAG) is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Memora - Personal Knowledge Base (RAG) support?

Memora - Personal Knowledge Base (RAG) is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Memora - Personal Knowledge Base (RAG)?

It is built and maintained by Probieren (@zzlzzlzzl15); the current version is v1.1.0.

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