# Weft

> Use this tool when you need to leverage local browsing history and knowledge graphs to inform AI decision-making. Weft enables AI assistants to access and search local browsing data, solving problems related to information retrieval and context-aware responses. It takes in MCP resources and tools as inputs, providing relevant outputs to enhance AI-driven interactions.

Canonical page: https://skillsregistry.net/skills/avi-141-weft  
JSON: https://api.skillsregistry.net/v1/skills/avi-141-weft

## Description

Enables AI assistants to access and search your local browsing knowledge graph via MCP resources and tools.

## Trust

- **Trust score (0–1):** 0.72
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-19

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/wmjrx3586u)
- **Repository:** <https://github.com/Avi-141/weft>

## 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": "avi-141-weft"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/avi-141-weft` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/avi-141-weft/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