# FeedRecall MCP Server

> FeedRecall MCP Server — paoladev45-feedrecall. Use this tool when you need to organize and retrieve personal content across projects, turning user interactions like likes and bookmarks into searchable data. The FeedRecall MCP Server solves the problem of fragmented personal content by providing a unified, project-aware memory that AI agents can access and process. It takes in user interaction data and outputs searchable, importable content through a local SQLite-backed interface.

Canonical page: https://skillsregistry.net/skills/paoladev45-feedrecall  
JSON: https://api.skillsregistry.net/v1/skills/paoladev45-feedrecall

## Description

Turns likes, bookmarks, and saved links into persistent project-aware memory, enabling AI agents to search, import, and process personal content through a local SQLite-backed MCP server.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-08-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/sex08ofqvq)
- **Repository:** <https://github.com/Paoladev45/feedrecall>

## 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": "paoladev45-feedrecall"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/paoladev45-feedrecall` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/paoladev45-feedrecall/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