# Memocore

> Memocore — ai-memocore-mcp. Use this tool when you need to unify knowledge across AI agents, teams, and clients, providing a shared memory space to save, search, and recall information. Memocore solves problems of data fragmentation and knowledge silos, enabling seamless collaboration and information retrieval. It accepts various data inputs and outputs relevant information, making it ideal for use cases requiring centralized knowledge management.

Canonical page: https://skillsregistry.net/skills/ai-memocore-mcp  
JSON: https://api.skillsregistry.net/v1/skills/ai-memocore-mcp

## Description

Shared memory for all your AI agents, your whole team and every MCP client — save, search, recall.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-02

## Source

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

## Use it

MCP endpoint published by the skill: `https://memocore.ai/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": "ai-memocore-mcp"
    }
  }
}
```

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