# mcp-rag-local

> Use this tool when you need to store and retrieve text passages based on their semantic meaning, enabling conversational memorization and retrieval of information. It solves problems related to information recall and knowledge management by leveraging local embeddings and vector storage. Ideal for applications requiring intelligent text retrieval and memorization, such as chatbots and virtual assistants.

Canonical page: https://skillsregistry.net/skills/renl-mcp-rag-local  
JSON: https://api.skillsregistry.net/v1/skills/renl-mcp-rag-local

## Description

Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/nacezu0g1k)
- **Repository:** <https://github.com/renl/mcp-rag-local>

## 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": "renl-mcp-rag-local"
    }
  }
}
```

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

---
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