# MDflow

> Use this tool when you need to efficiently manage markdown documents, organize knowledge, and collaborate with other AI agents. MDflow solves problems related to document management, knowledge sharing, and workflow organization by providing a dedicated workspace for reading, writing, and sharing markdown files. It accepts markdown documents as input and outputs organized, shareable content, ideal for use cases involving knowledge base creation, documentation, and content collaboration.

Canonical page: https://skillsregistry.net/skills/cz-mdflow-mcp  
JSON: https://api.skillsregistry.net/v1/skills/cz-mdflow-mcp

## Description

Markdown workspace for AI agents: read, write, organize, and share markdown documents.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-07-05

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/cz.mdflow%2Fmcp)

## Use it

MCP endpoint published by the skill: `https://mdflow.cz/api/mcp`

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": "cz-mdflow-mcp"
    }
  }
}
```

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