# Memograph

> Use this tool when you need to organize and query large amounts of markdown notes, converting them into a graph-based knowledge base for efficient retrieval and analysis. Memograph solves problems of information overload and disjointed note-taking, enabling seamless graph traversal, semantic search, and autonomous memory management. It takes in markdown notes and outputs a queryable knowledge base, ideal for use cases involving large language models and complex information networks.

Canonical page: https://skillsregistry.net/skills/indhar01-memograph  
JSON: https://api.skillsregistry.net/v1/skills/indhar01-memograph

## Description

Memograph transforms markdown notes into a queryable, graph-based knowledge base for large language models. It supports bidirectional wikilinks, hybrid retrieval combining keyword matching and graph traversal, and optional vector embeddings. The MCP server exposes 19 tools covering memory CRUD operations, graph traversal, semantic search, vault analytics, and autonomous memory management.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **Last scanned:** 2026-09-19

## Facts

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

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/indhar01-memograph)
- **Repository:** <https://github.com/indhar01/memograph>

## 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": "indhar01-memograph"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/indhar01-memograph` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/indhar01-memograph/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