# RAG Context

> Use this tool when you need to manage persistent memory and context for AI assistants, enabling semantic search and retrieval of stored information while maintaining user privacy and data control. It solves problems such as remembering user preferences and project configurations across conversations, and offers inputs including text data and configurable similarity thresholds, with outputs of relevant contextual information. Ideal for use cases requiring local, reliable, and efficient storage and retrieval of contextual data.

Canonical page: https://skillsregistry.net/skills/rag-context  
JSON: https://api.skillsregistry.net/v1/skills/rag-context

## Description

This MCP server provides persistent memory and context management for AI assistants using local vector storage and SQLite database, enabling semantic search and indexed retrieval of stored information. Built with TypeScript using Vectra for vector similarity search and Xenova/all-MiniLM-L6-v2 for local text embeddings, it offers two core tools: setContext for storing information with automatic vectorization and metadata support, and getContext for retrieving relevant context through hybrid semantic search with configurable similarity thresholds. The implementation runs entirely locally with no external API calls, storing data in a user-specified directory with SQLite for reliable persistence and vector indices for efficient similarity search, making it valuable for AI assistants that need to remember user preferences, project configurations, coding patterns, and other contextual information across conversations while maintaining complete privacy and data control.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/rag-context)
- **Repository:** <https://github.com/notbnull/mcp-rag-context>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "rag-context"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/rag-context` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/rag-context/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt