# Memory-MCP

> Use this tool when you need to retain insights and solutions across coding sessions, or when debugging complex issues that require persistent memory. Memory-MCP solves problems of knowledge loss and repetition by storing and retrieving patterns, solutions, and insights using hybrid search and neural reranking. It takes in coding session data as input and outputs relevant information, making it ideal for use in iterative development and troubleshooting contexts.

Canonical page: https://skillsregistry.net/skills/wb200-memory-mcp  
JSON: https://api.skillsregistry.net/v1/skills/wb200-memory-mcp

## Description

Provides persistent memory for AI agents using hybrid search (vector embeddings + BM25) with neural reranking, enabling storage and retrieval of insights, debugging solutions, and patterns across coding sessions.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/vff01462qo)
- **Repository:** <https://github.com/wb200/memory-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": "wb200-memory-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wb200-memory-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wb200-memory-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