# ai.smithery/ProfessionalWiki-mediawiki-mcp-server

> Use this tool when you need to integrate Large Language Models with MediaWiki wikis, enabling seamless interaction and automation of tasks such as content creation, editing, and retrieval. It solves problems of manual data transfer and formatting, allowing for efficient knowledge management and updates. The tool accepts inputs from LLM clients and outputs formatted data to the MediaWiki wiki, ideal for use cases requiring automated wiki management and curation.

Canonical page: https://skillsregistry.net/skills/ai-smithery-professionalwiki-mediawiki-mcp-server  
JSON: https://api.skillsregistry.net/v1/skills/ai-smithery-professionalwiki-mediawiki-mcp-server

## Description

Enable Large Language Model clients to interact seamlessly with any MediaWiki wiki. Perform action…

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 0.1.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-02

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.smithery%2FProfessionalWiki-mediawiki-mcp-server)

## Use it

MCP endpoint published by the skill: `https://server.smithery.ai/@ProfessionalWiki/mediawiki-mcp-server/mcp`

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": "ai-smithery-professionalwiki-mediawiki-mcp-server"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ai-smithery-professionalwiki-mediawiki-mcp-server` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ai-smithery-professionalwiki-mediawiki-mcp-server/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