# srs-mcp

> Use this tool when you need to implement efficient learning and memory retention strategies through spaced repetition. It solves problems of knowledge retention and recall by optimizing review schedules, and accepts inputs such as new cards and recall grades, producing outputs like due cards and learning progress. Ideal for use in applications requiring adaptive learning and long-term knowledge retention.

Canonical page: https://skillsregistry.net/skills/klutometis-srs-mcp  
JSON: https://api.skillsregistry.net/v1/skills/klutometis-srs-mcp

## Description

Enables agents to perform spaced-repetition learning with FSRS scheduling, including adding cards, reviewing due cards, and grading recall, using a headless SQLite or Postgres backend.

## Trust

- **Trust score (0–1):** 0.68
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/fzjlfrhjz1)
- **Repository:** <https://github.com/klutometis/srs-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": "klutometis-srs-mcp"
    }
  }
}
```

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