# LLM Wiki Streamable HTTP MCP Server

> LLM Wiki Streamable HTTP MCP Server — shinerio-llm-wiki-streamable-http-mcp. Use this tool when you need to access and query a knowledge base remotely, or integrate LLM Wiki capabilities into other applications via a secure API. It solves problems of remote access and integration by providing a streamable HTTP interface for listing projects, reading files, searching, and querying knowledge graphs. Ideal for use cases requiring programmatic access to LLM Wiki functionality, such as automated data retrieval or API-based application development.

Canonical page: https://skillsregistry.net/skills/shinerio-llm-wiki-streamable-http-mcp  
JSON: https://api.skillsregistry.net/v1/skills/shinerio-llm-wiki-streamable-http-mcp

## Description

Exposes LLM Wiki desktop capabilities via Streamable HTTP transport for MCP clients, enabling project listing, file reading, search, and knowledge graph queries through a secure API.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-30

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-08-30

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/on78xp9c61)
- **Repository:** <https://github.com/shinerio/llm-wiki-streamable-http-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": "shinerio-llm-wiki-streamable-http-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/shinerio-llm-wiki-streamable-http-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/shinerio-llm-wiki-streamable-http-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