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2dogsandanerd

ClawRAG - Self-hosted RAG & Memory

by 2dogsandanerd · GitHub ↗ · v1.2.0
cross-platform ⚠ suspicious
1549
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0
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8
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Install in OpenClaw
/install clawrag
Description
Self-hosted RAG engine with hybrid semantic and keyword search, document ingestion, local privacy, and seamless OpenClaw integration via Docker.
README (SKILL.md)

ClawRAG Connector

The Brain for OpenClaw - Self-hosted RAG engine with hybrid search.

⚠️ This skill requires Docker. It connects OpenClaw to your local ClawRAG instance.

What is ClawRAG?

Production-ready RAG infrastructure that keeps your data local:

  • 🔒 Privacy-first: Vector DB runs on your machine
  • 🔍 Hybrid Search: Semantic + Keyword (BM25) + RRF ranking
  • 📄 Smart Ingestion: PDFs, Office docs, Markdown via Docling
  • 🧠 MCP-native: Seamless OpenClaw integration

Installation

Step 1: Start ClawRAG (Docker)

git clone https://github.com/2dogsandanerd/ClawRag.git
cd ClawRag
cp .env.example .env
docker compose up -d

Wait for http://localhost:8080/health to return OK.

Step 2: Connect OpenClaw

openclaw mcp add --transport stdio clawrag npx -y @clawrag/mcp-server

Verification

Test your setup:

curl http://localhost:8080/api/v1/rag/collections

Features

Capability Description
Document Upload PDF, DOCX, TXT, MD via API or folder
Hybrid Query Vector similarity + keyword matching
Citations Source tracking for all answers
Multi-Collection Organize knowledge by project

Requirements

  • Docker + Docker Compose
  • 4GB+ RAM (8GB recommended for local LLM)
  • Or: OpenAI/Anthropic API key for cloud LLM

Architecture

OpenClaw ◄──MCP──► @clawrag/mcp-server ◄──HTTP──► ClawRAG API (localhost:8080)
                                           │
                                           ▼
                                    ┌─────────────┐
                                    │  ChromaDB   │
                                    │  (vectors)  │
                                    └─────────────┘

Links

Tags

rag, vector, memory, search, documents, self-hosted, privacy, mcp, local-ai


Metadata für ClawHub-Upload:

Feld Wert
Slug clawrag
Display name ClawRAG - Self-hosted RAG & Memory
Version 1.2.0
Tags rag, vector, memory, search, documents, self-hosted, privacy, mcp, local-ai

Changelog für Version 1.2.0

1.2.0 - Initial ClawHub Release

  • Connector skill for OpenClaw integration
  • MCP server support (@clawrag/mcp-server v1.1.0)
  • Docker-first deployment
  • Hybrid search (Vector + BM25)
Usage Guidance
This connector is plausible for a self‑hosted RAG setup, but take these precautions before installing: - Expect to run Docker and docker‑compose; the skill metadata failed to list Docker as a requirement. Don't run it on a critical host without isolation. - The instructions clone a personal GitHub repo and call npx to fetch a package — review the repository and the npm package code, or inspect the package contents locally, before executing. npx will run code fetched from npm. - Check the .env.example file (do not blindly copy secrets). The skill mentions OpenAI/Anthropic API keys which are sensitive; only provide keys if you understand why they're needed and consider using limited/rotated keys. - Inspect which Docker images the compose file pulls; untrusted images can execute arbitrary code on your machine. Prefer running in a sandboxed VM or dedicated host. - Verify the project’s maintainer reputation, GitHub commit history, and npm package versions (avoid unpublished or unverified packages if possible). If you want a lower‑risk path: deploy to an isolated environment, audit the repo and docker compose YAML, and supply only the minimal credentials required.
Capability Analysis
Type: OpenClaw Skill Name: clawrag Version: 1.2.0 The skill bundle is classified as suspicious due to its reliance on fetching and executing external code from various sources. The `SKILL.md` instructs the AI agent/user to perform `git clone` from a GitHub repository (github.com/2dogsandanerd/ClawRag.git), execute `docker compose up -d` which pulls and runs Docker images, and run `npx @clawrag/mcp-server` to install and execute an npm package. While these actions are plausibly needed for the stated purpose of setting up a local RAG service, they introduce a significant supply chain risk as the integrity of these external dependencies (GitHub repo, Docker images, npm package) cannot be guaranteed by the skill bundle itself. There is no clear evidence of intentional malicious behavior within the provided files, nor any prompt injection attempts to subvert the agent's core function.
Capability Assessment
Purpose & Capability
The SKILL.md describes a ClawRAG connector (self‑hosted RAG via Docker, an MCP server) which aligns with the skill name. However the registry metadata provides no description and omits expected requirements (Docker, docker-compose). This mismatch is an authoring/metadata gap rather than an obvious functional mismatch.
Instruction Scope
Instructions are narrowly scoped to: clone a GitHub repo, copy .env.example -> .env, run docker compose, add an MCP via npx, and verify the local HTTP health endpoint. They do not instruct reading unrelated host files or exfiltrating data, but they do require executing network‑fetched code and running containers on the host.
Install Mechanism
There is no formal install spec, but runtime steps fetch code from a personal GitHub repo (https://github.com/2dogsandanerd/ClawRag.git), run docker compose (images unspecified), and invoke npx to fetch @clawrag/mcp-server from npm. Those are legitimate for this purpose but involve running unreviewed third‑party code and container images — higher risk than an instruction‑only skill that uses only built‑in tooling.
Credentials
Registry metadata declares no required environment variables, but SKILL.md states you may need OpenAI/Anthropic API keys (and creates a .env from .env.example). This is an inconsistency: the skill may require sensitive API keys and environment configuration that are not declared in metadata, so users might be surprised to need to provide secrets.
Persistence & Privilege
The skill does not request always:true and does not claim to modify other skills or system settings. It does ask you to register an MCP connector via openclaw mcp add (expected for its purpose). Autonomous invocation is allowed (platform default) but not a new privilege here.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install clawrag
  3. After installation, invoke the skill by name or use /clawrag
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.2.0
ClawRAG Connector 1.2.0 – Initial ClawHub release. - Adds OpenClaw connector skill for local, privacy-first RAG infrastructure. - Integrates MCP server support via @clawrag/mcp-server. - Supports Docker-based deployment. - Enables hybrid search (semantic + BM25) and smart ingestion of common document formats.
Metadata
Slug clawrag
Version 1.2.0
License
All-time Installs 8
Active Installs 8
Total Versions 1
Frequently Asked Questions

What is ClawRAG - Self-hosted RAG & Memory?

Self-hosted RAG engine with hybrid semantic and keyword search, document ingestion, local privacy, and seamless OpenClaw integration via Docker. It is an AI Agent Skill for Claude Code / OpenClaw, with 1549 downloads so far.

How do I install ClawRAG - Self-hosted RAG & Memory?

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

Is ClawRAG - Self-hosted RAG & Memory free?

Yes, ClawRAG - Self-hosted RAG & Memory is completely free (open-source). You can download, install and use it at no cost.

Which platforms does ClawRAG - Self-hosted RAG & Memory support?

ClawRAG - Self-hosted RAG & Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created ClawRAG - Self-hosted RAG & Memory?

It is built and maintained by 2dogsandanerd (@2dogsandanerd); the current version is v1.2.0.

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