# journal-rag

> Use this tool when you need to efficiently search and retrieve information from team markdown journals, leveraging advanced algorithms like BM25 and local vector embeddings. It solves problems of knowledge discovery and organization, enabling users to quickly find relevant information through search, browse, and regex lookup functionalities. Ideal for teams with large collections of markdown journals, it accepts query inputs and returns relevant journal entries as outputs.

Canonical page: https://skillsregistry.net/skills/neryams-workspace-docs-mcp  
JSON: https://api.skillsregistry.net/v1/skills/neryams-workspace-docs-mcp

## Description

Hybrid retrieval MCP server for searching team markdown journals using BM25 and local vector embeddings, with tools for search, browse, and regex lookup.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/m7070b810x)
- **Repository:** <https://github.com/neryams/workspace-docs-mcp>

## 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": "neryams-workspace-docs-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/neryams-workspace-docs-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/neryams-workspace-docs-mcp/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