# Paperclip Surfers

> Use this tool when you need to manage and optimize AI agent companies with persistent conversations and scalable memory. It solves problems related to agent performance, tool assignment, and skill selection, providing a centralized control plane with analytics and self-improvement capabilities. Ideal for use cases requiring multi-agent orchestration, customizable tooling, and data-driven decision making.

Canonical page: https://skillsregistry.net/skills/incomestreamsurfer-paperclip-surfers  
JSON: https://api.skillsregistry.net/v1/skills/incomestreamsurfer-paperclip-surfers

## Description

A control plane for managing AI agent companies with persistent conversations, global and project-scoped agent memory, per-agent tool assignment, skills selection, performance KPIs, and a self-improvement loop. Fork of paperclipai/paperclip with added memory persistence, tool discovery, and analytics dashboard. Built with TypeScript and deployable via Docker.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** cloud-infra
- **Updated:** 2026-05-18

## Source

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

## 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": "incomestreamsurfer-paperclip-surfers"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/incomestreamsurfer-paperclip-surfers` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/incomestreamsurfer-paperclip-surfers/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