# mcp-logseq

> mcp-logseq — ergut-mcp-logseq. Use this tool when you need to integrate AI assistants with LogSeq, enabling seamless interaction with your graph data. It solves problems of data accessibility and management by providing a Local HTTP API interface for reading, writing, and managing LogSeq data. With inputs of API requests and outputs of graph data, use mcp-logseq to bridge AI capabilities with LogSeq functionality.

Canonical page: https://skillsregistry.net/skills/ergut-mcp-logseq  
JSON: https://api.skillsregistry.net/v1/skills/ergut-mcp-logseq

## Description

MCP server to interact with LogSeq via its Local HTTP API - enabling AI assistants like Claude to seamlessly read, write, and manage your LogSeq graph.

## Trust

- **Trust score (0–1):** 0.14
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/ergut/mcp-logseq)

## 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": "ergut-mcp-logseq"
    }
  }
}
```

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