# linked-docs

> Use this tool when you need to efficiently search and reference large documentation sets, as it solves the problem of information overload by providing hybrid semantic and keyword search capabilities. It takes in natural language queries as input and outputs relevant document references via the MCP protocol. Ideal for use cases where AI assistants require accurate and context-specific information retrieval.

Canonical page: https://skillsregistry.net/skills/folence-linked-docs-mcp  
JSON: https://api.skillsregistry.net/v1/skills/folence-linked-docs-mcp

## Description

Enables AI assistants to intelligently search and reference documentation using hybrid semantic + keyword search via MCP protocol.

## Trust

- **Trust score (0–1):** 0.67
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/qt60lua07y)
- **Repository:** <https://github.com/folence/Linked-Docs-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": "folence-linked-docs-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/folence-linked-docs-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/folence-linked-docs-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