F
licenseNot graded
qualityD
maintenanceAI-powered n8n documentation server that enables intelligent semantic search and retrieval of node configurations, workflows, and templates for AI assistants.
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n8n-asistans
by onurpolat05
n8nアシスタント
このプロジェクトには、n8nと統合されたアシスタントを作成するためのマルチチャネルプラットフォーム（MCP）サーバーが含まれています。このアシスタントは、n8nのドキュメント、サンプルワークフロー、コミュニティフォーラムを検索するために使用できます。
特徴
Web 検索: 特定のクエリに基づいて、n8n のドキュメント、ワークフロー、コミュニティ フォーラムを検索します。
HTML コンテンツの取得: BeautifulSoup を使用して検索結果からメインコンテンツを抽出します。
非同期処理: HTTP リクエストを非同期的に実行し、応答時間を短縮します。
Related MCP server: n8n MCP Server
要件
Python 3.7以上
httpxライブラリbeautifulsoup4ライブラリpython-dotenvライブラリ
インストール
Smithery経由でインストール
Smithery経由で Claude Desktop 用の n8n-assistant を自動的にインストールするには:
npx -y @smithery/cli install @onurpolat05/n8n-assistant --client claude手動インストール
このリポジトリをクローンします:
git clone <repository-url> cd <repository-directory>必要な依存関係をインストールします。
pip install -r requirements.txt.envファイルを作成し、必要な API キーを追加します。SERPER_API_KEY=your_api_key_here
使用法
アシスタントを起動するには、次のコマンドを実行します。
uvicorn main:app --reload次に、次のようにしてアシスタントに n8n に関連する情報を照会できます。
await get_n8n_info("HTTP Request node", "docs")MCPサーバー
このプロジェクトではn8n-asistans MCPサーバーを使用します。サーバーは次のコマンドで起動します。
{
"mcpServers": {
"n8n-asistans": {
"command": "uv",
"args": [
"--directory",
"/n8n-assistant",
"run",
"main.py"
],
"env":{
"SERPER_API_KEY": "*********"
}
}
}
}貢献
貢献したい場合は、プルリクエストを作成するか、問題を報告してください。
ライセンス
このプロジェクトは MIT ライセンスに基づいてライセンスされています。
Available Tools
1 toolget_n8n_infoB
Search the latest n8n resources for a given query.
Args: query: The query to search for (e.g. "HTTP Request node") resource_type: The resource type to search in (docs, workflows, community) - docs: General n8n documentation - workflows: Example workflows (will search for "n8n example {query}") - community: Community forums for issues and questions
Returns: Text from the n8n resources
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | ||
| resource_type | Yes |
TDQS
B3.3/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'latest n8n resources' but lacks details on permissions, rate limits, error handling, or response format beyond 'Text from the n8n resources,' leaving significant gaps for a search tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with a purpose statement, args section, and returns section, making it easy to parse. It could be slightly more concise by integrating the parameter details more fluidly, but overall it's efficient with minimal waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations, no output schema, and low complexity, the description covers the basic purpose and parameters adequately. However, it lacks details on behavioral aspects like search limitations or result formatting, making it minimally viable but incomplete for optimal agent use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at 0%, the description fully compensates by clearly explaining both parameters: 'query' as the search term with an example and 'resource_type' with detailed options (docs, workflows, community) and their meanings. This adds substantial value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose as 'Search the latest n8n resources for a given query,' which specifies the verb (search) and resource (n8n resources). However, with no sibling tools provided, it cannot demonstrate differentiation from alternatives, preventing a perfect score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It only lists parameters and returns, offering no context for decision-making in usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
1 tool update
- First observed
get_n8n_info
TDQS
B3.4/5.0
Scored across 1 tool
Disambiguation5/5
With only one tool, there is no possibility of ambiguity or overlap between tools, making disambiguation perfect. The tool's purpose is clearly defined as searching n8n resources, and no other tools exist to cause confusion.
Naming Consistency5/5
Since there is only one tool, naming consistency is inherently perfect with no deviations or mixed conventions to evaluate. The tool name 'get_n8n_info' follows a clear verb_noun pattern, but consistency across multiple tools cannot be assessed.
Tool Count2/5
A single tool for a server named 'n8n-asistans' feels too thin for the apparent scope, as it only offers search functionality without any CRUD operations or broader management capabilities for n8n resources. This is a borderline case leaning toward inadequacy for a typical assistant server.
Completeness2/5
The tool surface is severely incomplete for an assistant server, as it only provides search functionality without any ability to create, update, delete, or manage n8n workflows or resources. This will likely cause agent failures when trying to perform comprehensive tasks beyond simple queries.
Maintenance
ActivityInactive
ResponsivenessNo issues
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