DocGen MCP Server
DocGen MCP サーバー
ソース ファイルから自動的にドキュメントを作成するためのドキュメント ジェネレーター MCP サーバー。
概要
DocGen MCPサーバーは、ソースファイルから情報を抽出し、テンプレートを適用することで、標準化されたドキュメントの作成を自動化します。他のMCPサーバー(Google Drive、GitHub、Perplexity)とシームレスに統合され、包括的なソリューションを提供します。
Related MCP server: RAG Documentation MCP Server
特徴
GitHubリポジトリとGoogleドライブファイルから情報を抽出する
複数のソースタイプ(スクリプト、プレゼンテーション、コード、参照ドキュメント)を処理する
テンプレートベースのドキュメント生成
ドキュメント履歴の追跡
Perplexity 統合による AI 強化コンテンツ生成
インストール
前提条件
Node.js 16以上
npmまたはyarn
Google Drive API へのアクセス(Google Drive ソース抽出用)
GitHub API へのアクセス (GitHub ソース抽出用)
手順
リポジトリをクローンします。
git clone https://github.com/rjadhav/docgen-mcp.git cd docgen-mcp依存関係をインストールします:
npm installプロジェクトをビルドします。
npm run buildMCP 設定ファイルに以下を追加します:
クロードデスクトップ向け
~/Library/Application Support/Claude/claude_desktop_config.jsonを編集します。
{
"mcpServers": {
"docgen-mcp": {
"command": "node",
"args": ["/path/to/docgen-mcp/build/index.js"],
"env": {},
"disabled": false,
"autoApprove": []
}
}
}VSCode Clineの場合
VSCode Claude Dev 拡張機能の MCP 設定ファイルを編集します。
{
"mcpServers": {
"docgen-mcp": {
"command": "node",
"args": ["/path/to/docgen-mcp/build/index.js"],
"env": {},
"disabled": false,
"autoApprove": []
}
}
}使用法
DocGen MCP サーバーは次のツールを公開します。
ドキュメント作成
テンプレートを使用してソース ファイルからドキュメントを生成します。
リストテンプレート
利用可能なドキュメント テンプレートを一覧表示します。
ドキュメント履歴の表示
以前に生成されたドキュメントの履歴を表示します。
テンプレート
テンプレートはtemplatesディレクトリに保存され、コンテンツ生成にはシンプルなマーカー システムが使用されます。
glama-ai- プロジェクト識別子に置き換えられました{{date}}- 現在の日付{{section:NAME}}- 名前付きセクションの生成されたコンテンツに置き換えられます
テンプレート ディレクトリに新しい.templateファイルを作成することで、カスタム テンプレートを追加できます。
貢献
貢献を歓迎します!お気軽にプルリクエストを送信してください。
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 - 詳細については LICENSE ファイルを参照してください。
Available Tools
3 toolscreate_documentationC
Create documentation from source files using a template
| Name | Required | Description | Default |
|---|---|---|---|
| output_path | No | Path where to save the generated documentation | |
| project_id | Yes | Project identifier (e.g., "JUVR058") | |
| sources | Yes | ||
| template_type | Yes | Type of documentation template to use (e.g., "CRISPRseq_Analysis") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'Create documentation' which implies a write/mutation operation, but doesn't disclose critical behavioral traits such as whether this requires specific permissions, what happens if documentation already exists at the output path (overwrites?), or any rate limits/constraints. The description adds minimal context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that front-loads the core action ('Create documentation') and includes essential elements ('from source files using a template') without any wasted words. It's appropriately sized for the tool's complexity and gets straight to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (4 parameters, no annotations, no output schema, and a write operation), the description is insufficiently complete. It doesn't explain what the tool returns (e.g., success confirmation, error details), behavioral implications of the mutation, or how parameters interact. For a documentation generation tool with multiple inputs, more context is needed to guide effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description mentions 'source files' and 'template' which loosely map to the 'sources' and 'template_type' parameters, but doesn't add meaningful semantics beyond what the schema provides (e.g., schema already describes template_type as 'Type of documentation template to use'). With 75% schema description coverage, the baseline is 3, and the description doesn't significantly compensate for the 25% gap or enhance parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Create documentation') and resources involved ('from source files using a template'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from its siblings (list_templates, view_document_history), which would require mentioning it's a generation/write operation versus listing or viewing operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention prerequisites (e.g., needing existing templates or source files), compare to sibling tools, or specify scenarios where this tool is appropriate versus others, leaving the agent with no contextual usage information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_templatesC
List available documentation templates
| Name | Required | Description | Default |
|---|---|---|---|
| category | No | Optional category to filter templates |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the action ('List') but doesn't describe traits like whether this is a read-only operation, how results are returned (e.g., pagination, format), or any limitations (e.g., rate limits). This is a significant gap for a tool with zero annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence with zero waste. It's appropriately sized for a simple tool and front-loaded with the core purpose, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'available documentation templates' entails (e.g., format, metadata), return values, or behavioral context, leaving gaps for a tool that likely returns a list of resources.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the single parameter 'category' documented as 'Optional category to filter templates'. The description doesn't add any meaning beyond this, such as examples of categories or filtering behavior, so it meets the baseline for high schema coverage without compensating further.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List') and resource ('available documentation templates'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'view_document_history' which might also involve listing documentation-related items, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives like 'create_documentation' or 'view_document_history'. The description lacks context about prerequisites, timing, or exclusions, leaving the agent with minimal usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
view_document_historyB
View history of previously generated documents
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of history entries to return | |
| project_id | No | Filter by project ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states 'view history', implying a read-only operation, but doesn't specify if it requires authentication, has rate limits, or what the return format looks like (e.g., pagination, error handling). This is a significant gap for a tool with no annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence that directly states the tool's purpose without any wasted words. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavioral traits and usage context, which are important for an agent to operate effectively without structured annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, clearly documenting both parameters ('limit' and 'project_id'). The description adds no additional semantic information beyond what the schema provides, such as default values or usage examples, so it meets the baseline score when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('view') and resource ('history of previously generated documents'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'list_templates' or 'create_documentation', which could also involve document-related operations, so it doesn't reach the highest score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
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. It doesn't mention sibling tools like 'list_templates' or 'create_documentation', nor does it specify prerequisites or contexts for usage, leaving the agent to infer based on tool names alone.
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.
3 tool updates
v1.0.0- First observed
create_documentation - First observed
list_templates - First observed
view_document_history
TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: create_documentation generates new docs, list_templates shows available templates, and view_document_history accesses past outputs. There is no overlap or ambiguity between these functions.
All tools follow a consistent verb_noun pattern (create_documentation, list_templates, view_document_history) with snake_case throughout. The naming is predictable and readable.
With only 3 tools, the set feels thin for a documentation generation server. While it covers core operations, more tools might be expected for tasks like updating templates, deleting documents, or customizing generation parameters.
The tools cover creation, template listing, and history viewing, but there are notable gaps: no update or delete operations for documents or templates, and no way to customize generation beyond templates. This could limit agent workflows.
Related MCP Connectors
Generate, search, and manage codebase documentation on DocuWriter.ai. 72 tools incl. Autopilot.
Versioned documentation registry and semantic search for AI tools and coding assistants.
Create, review and edit Word, PowerPoint, Excel and PDF documents from any AI agent.
81Generate wiki docs from source code. Supports PowerShell, Python, Go, C#, Java, COBOL.
Related MCP Servers
- AlicenseBqualityNot gradedmaintenanceProvides tools for collecting and documenting code from directories.457 npm15MIT
- AlicenseAqualityDmaintenanceProvides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.711 npm1MIT
- AlicenseNot gradedqualityDmaintenanceAutomates the creation of application user manuals by capturing screenshots and generating documentation, supporting any web application through configurable workflows and MCP integration with AI assistants.MIT
- AlicenseNot gradedqualityDmaintenanceA sophisticated server that enables AI assistants to automatically analyze codebases and generate comprehensive, professional documentation.2MIT