Qiita MCP Server
The Qiita MCP Server is a Model Context Protocol server that provides comprehensive access to Qiita and Qiita Team articles through various search and retrieval tools.
Core Capabilities:
Search articles - Search by query string or retrieve recent articles, with pagination support (1-100 items per page)
Get specific articles - Retrieve detailed information about an article using its ID
Browse by tags - Find articles with specific tags (e.g., 'Python', 'JavaScript') with pagination
Browse by user - Get all articles written by a specific user with pagination
Explore tags - Retrieve a list of tags used in Qiita, sortable by usage count or name
Read comments - Access comments posted on a specific article
View user bookmarks - Retrieve articles that a user has stocked (bookmarked) with pagination
Additional Features:
Supports both public Qiita and private Qiita Team instances
Optional authentication with access tokens for higher rate limits
Type-safe validation using Zod
SSE (Server-Sent Events) communication for integration with Claude Desktop
Provides tools for searching and viewing Qiita articles, retrieving articles by tag or user, managing bookmarked articles (stocks), fetching comments, and accessing Qiita Team content.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Qiita MCP Serversearch for articles about TypeScript with the latest 10 results"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Qiita MCP Server
Qiita および Qiita Team の記事検索・閲覧機能を提供する MCP (Model Context Protocol) サーバー。
特徴
📖 記事の検索・閲覧
🏷️ タグによる絞り込み
👤 ユーザー別記事取得
💬 コメント取得
⭐ ストック(ブックマーク)記事の取得
🔒 Qiita Team 対応
⚡ Hono による高速なルーティング
✅ Zod による型安全なバリデーション
Related MCP server: Qiita API MCP Server
技術スタック
Hono: 軽量で高速な Web フレームワーク
Zod: TypeScript ファーストなスキーマバリデーション
MCP SDK: Model Context Protocol の公式 SDK
TypeScript: 型安全な開発
仕様書
詳細な仕様は docs/specification.md を参照してください。
インストール
npm install
npm run build起動
サーバーの起動
npm startデフォルトでは http://localhost:3000 で起動します。
環境変数
ポート設定(オプション)
export PORT=3000Qiita アクセストークン(オプション)
認証なしでも公開記事は閲覧できますが、レート制限が厳しくなります。 アクセストークンを設定することを推奨します。
export QIITA_ACCESS_TOKEN=your_access_token_hereアクセストークンは Qiita の設定ページ で取得できます。
Qiita Team(オプション)
Qiita Team を使用する場合は、チーム名を設定します。
export QIITA_TEAM=your_team_name環境変数を設定して起動
QIITA_ACCESS_TOKEN=your_token PORT=3000 npm startClaude Desktop での設定
本サーバーは SSE (Server-Sent Events) 方式で動作します。
Claude Desktop の設定ファイルに以下を追加します。
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"qiita": {
"url": "http://localhost:3000/sse"
}
}
}重要: Claude Desktop から接続する前に、サーバーを起動しておく必要があります。
サーバーを起動してから Claude Desktop を起動、またはリロードしてください。
環境変数付きで起動する場合
別のターミナルウィンドウで以下のコマンドを実行してサーバーを起動します:
QIITA_ACCESS_TOKEN=your_token npm startQiita Team を使用する場合:
QIITA_ACCESS_TOKEN=your_token QIITA_TEAM=your_team_name npm start提供されるツール
search_items
記事を検索します。
パラメータ:
query(string, optional): 検索クエリpage(number, optional): ページ番号(1-100、デフォルト: 1)per_page(number, optional): 1ページあたりの件数(1-100、デフォルト: 20)
使用例:
Qiita で「MCP Server」を検索してくださいget_item
特定の記事を取得します。
パラメータ:
item_id(string, required): 記事ID
使用例:
記事 ID が "abc123" の記事を表示してくださいget_items_by_tag
特定のタグが付いた記事を取得します。
パラメータ:
tag_id(string, required): タグIDpage(number, optional): ページ番号per_page(number, optional): 1ページあたりの件数
使用例:
Python タグの記事を表示してくださいget_items_by_user
特定のユーザーの記事を取得します。
パラメータ:
user_id(string, required): ユーザーIDpage(number, optional): ページ番号per_page(number, optional): 1ページあたりの件数
使用例:
ユーザー "example_user" の記事を表示してくださいget_tags
タグ一覧を取得します。
パラメータ:
page(number, optional): ページ番号per_page(number, optional): 1ページあたりの件数sort(string, optional): ソート順("count" または "name")
使用例:
人気のタグ一覧を表示してくださいget_item_comments
記事のコメントを取得します。
パラメータ:
item_id(string, required): 記事ID
使用例:
記事 "abc123" のコメントを表示してくださいget_user_stocks
ユーザーがストックした記事を取得します。
パラメータ:
user_id(string, required): ユーザーIDpage(number, optional): ページ番号per_page(number, optional): 1ページあたりの件数
使用例:
ユーザー "example_user" がストックした記事を表示してください開発
# ビルド
npm run build
# 開発モード(ウォッチモード)
npm run dev
# 起動
npm startライセンス
MIT
参考
Available Tools
7 toolsget_itemB
Get a specific Qiita article by its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Article ID |
TDQS
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 states this is a read operation ('Get'), but doesn't mention any behavioral traits like authentication requirements, rate limits, error handling, or what happens if the ID is invalid. For a tool with zero annotation coverage, this leaves significant gaps.
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 with zero wasted words. It's appropriately sized and front-loaded, making it easy to understand at a glance.
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?
For a simple read operation with one parameter and no output schema, the description is minimally adequate. However, with no annotations and siblings present, it lacks context about when to use it versus alternatives and behavioral details like error responses, leaving room for improvement.
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 'item_id' clearly documented as 'Article ID' in the schema. The description adds no additional parameter semantics beyond what's already in the schema, so it meets the baseline score when schema coverage is high.
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 ('Get') and resource ('a specific Qiita article by its ID'), making the purpose immediately understandable. However, it doesn't explicitly differentiate this tool from its siblings like 'get_items_by_tag' or 'search_items' beyond the ID specificity, which prevents 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.
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. With siblings like 'get_items_by_tag' and 'search_items' available, there's no indication that this tool is specifically for retrieving a single known article by ID rather than searching or filtering by other criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_item_commentsB
Get comments on a specific article.
| Name | Required | Description | Default |
|---|---|---|---|
| item_id | Yes | Article ID |
TDQS
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. While 'Get comments' implies a read-only operation, it doesn't specify whether authentication is required, if there are rate limits, what format the comments are returned in (e.g., structured list, raw text), or if there are any constraints like pagination. This leaves significant gaps in understanding the tool's behavior.
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, clear sentence that directly states the tool's purpose without any unnecessary words. It's front-loaded with the core action ('Get comments'), making it efficient and easy to parse, which is ideal for conciseness.
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?
For a simple read operation with one well-documented parameter and no output schema, the description is minimally adequate. However, it lacks details on behavioral aspects (e.g., authentication, return format) and usage context compared to siblings, which are important for an AI agent to use it effectively. The absence of annotations and output schema means the description should compensate more than it does.
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?
Schema description coverage is 100%, with the single parameter 'item_id' clearly documented as 'Article ID' in the schema. The description adds no additional meaning beyond this, such as format examples (e.g., numeric vs. string IDs) or context on where to find the ID. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles the parameter documentation adequately.
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 ('Get') and resource ('comments on a specific article'), making the purpose immediately understandable. However, it doesn't differentiate this tool from potential sibling tools that might also retrieve comments or related data, such as 'get_item' which might include comments as part of a broader item retrieval.
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. Given sibling tools like 'get_item' (which might retrieve the article itself, possibly including comments) and 'search_items' (which might filter articles), there's no indication of when this specific comment-focused tool is preferred or necessary over those alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_items_by_tagC
Get Qiita articles with a specific tag.
| Name | Required | Description | Default |
|---|---|---|---|
| tag_id | Yes | Tag ID (e.g., 'Python', 'JavaScript') | |
| page | No | Page number (1-100, default: 1) | |
| per_page | No | Items per page (1-100, default: 20) |
TDQS
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 'Get' which implies a read operation, but doesn't cover important aspects like rate limits, authentication requirements, pagination behavior (beyond what the schema hints at), or error handling. This is inadequate for a tool with no annotation support.
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 unnecessary 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 lack of annotations and output schema, the description is insufficient. It doesn't explain what the return format looks like (e.g., list of articles with fields), error conditions, or behavioral constraints. For a tool with 3 parameters and no structured output documentation, more context is needed.
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 clear documentation for all parameters (tag_id, page, per_page). The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 for high schema coverage without providing extra value.
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 'Get' and the resource 'Qiita articles with a specific tag', making the purpose understandable. However, it doesn't explicitly distinguish this tool from sibling tools like 'search_items' or 'get_items_by_user', which might also retrieve articles based on different criteria.
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 like 'search_items' or 'get_items_by_user'. It lacks context about scenarios where filtering by tag is preferred over other search methods, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_items_by_userC
Get articles written by a specific user.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | User ID | |
| page | No | Page number (1-100, default: 1) | |
| per_page | No | Items per page (1-100, default: 20) |
TDQS
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 states the action but lacks details on permissions, rate limits, pagination behavior (beyond what the schema implies), or response format. This is inadequate for a tool with multiple parameters and no output schema.
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, clear sentence with no wasted words. It's front-loaded with the core purpose, making it efficient and easy to parse, which is ideal for conciseness.
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 has 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the return values (e.g., article details), error conditions, or usage nuances, leaving significant gaps for an AI agent to operate effectively.
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%, so the schema already documents all parameters (user_id, page, per_page) with descriptions and constraints. The description adds no additional meaning beyond implying user-based filtering, which is redundant with the schema, meeting the baseline for high coverage.
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 ('Get') and resource ('articles written by a specific user'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_items_by_tag' or 'search_items', which also retrieve items but with different filters, so it falls short of 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.
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. For example, it doesn't mention when to choose 'get_items_by_user' over 'search_items' for user-specific queries or 'get_item' for individual articles, leaving the agent without context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tagsC
Get a list of tags used in Qiita.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number (1-100, default: 1) | |
| per_page | No | Items per page (1-100, default: 20) | |
| sort | No | Sort order: 'count' (by item count) or 'name' (default: 'count') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions 'list of tags' which implies a read operation, but doesn't disclose pagination behavior, rate limits, authentication requirements, or what the response format looks like. For a tool with 3 parameters and no output schema, this leaves significant behavioral gaps.
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, clear sentence with zero wasted words. It's appropriately sized for a simple list operation and front-loads the core purpose immediately.
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?
For a tool with 3 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain the paginated nature of the response, what fields tags include, or how this differs from related operations. The agent would need to guess about the return format and behavioral details.
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?
Schema description coverage is 100%, so all parameters are documented in the schema. The description adds no additional parameter information beyond what's already in the schema, which meets the baseline expectation but doesn't provide extra value.
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 ('Get') and resource ('list of tags used in Qiita'), making the purpose immediately understandable. However, it doesn't differentiate from sibling tools like 'get_items_by_tag' or 'search_items', which prevents 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.
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. With sibling tools like 'get_items_by_tag' and 'search_items' available, the agent receives no help in choosing between listing tags versus retrieving items filtered by tags.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_user_stocksC
Get articles that a user has stocked (bookmarked).
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes | User ID | |
| page | No | Page number (1-100, default: 1) | |
| per_page | No | Items per page (1-100, default: 20) |
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 ('Get articles') but does not cover critical aspects like whether this is a read-only operation, potential rate limits, authentication needs, or what the return format looks like (e.g., list of articles with details). This leaves significant gaps for a tool with three parameters.
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 unnecessary words. It is front-loaded and wastes no space, making it highly concise and well-structured for quick understanding.
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 complexity of a tool with three parameters, no annotations, and no output schema, the description is incomplete. It fails to explain behavioral traits, return values, or usage context, which are essential for an agent to invoke the tool correctly and handle its output. The high schema coverage does not compensate for these missing elements.
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%, meaning all parameters are documented in the schema itself. The description does not add any additional meaning beyond implying that 'user_id' identifies the user whose stocked articles are retrieved, which is already clear from the schema. Thus, it meets the baseline for adequate but not enhanced parameter semantics.
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 ('Get') and resource ('articles that a user has stocked'), making the purpose specific and understandable. However, it does not explicitly differentiate from sibling tools like 'get_items_by_user' or 'search_items', which might also retrieve user-related content, so it falls short of 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.
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, such as how it differs from 'get_items_by_user' or 'search_items'. It lacks explicit context, prerequisites, or exclusions, leaving the agent to infer usage based on the tool name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_itemsB
Search Qiita articles. You can search with a query string or get recent articles without a query.
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search query (optional) | |
| page | No | Page number (1-100, default: 1) | |
| per_page | No | Items per page (1-100, default: 20) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the tool can 'search' or 'get recent articles', but doesn't disclose behavioral traits such as whether it's read-only, if it requires authentication, rate limits, pagination behavior beyond parameters, or what the return format looks like. This is a significant gap for a search 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 front-loads the purpose and usage, with zero wasted words. It clearly communicates the core functionality without unnecessary details.
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 (search functionality with 3 parameters), no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects like authentication needs, rate limits, return format, and error handling, which are crucial for an AI agent to use it correctly.
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%, so the schema already documents all parameters (query, page, per_page) with descriptions and constraints. The description adds no additional meaning beyond implying query is optional for getting recent articles, which is already covered in the schema. Baseline 3 is appropriate 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 verb ('search') and resource ('Qiita articles'), specifying it can search with a query or get recent articles without one. However, it doesn't explicitly differentiate from siblings like 'get_items_by_tag' or 'get_items_by_user', which are more specific search variants.
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 implies usage by mentioning 'search with a query string or get recent articles without a query', which suggests when to use it (for general searches or recent articles). However, it doesn't provide explicit guidance on when to use this vs. alternatives like 'get_items_by_tag' for tag-based searches, leaving some ambiguity.
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.
7 tool updates
v1.0.0- First observed
get_item - First observed
get_item_comments - First observed
get_items_by_tag - First observed
get_items_by_user - First observed
get_tags - First observed
get_user_stocks - First observed
search_items
TDQS
Scored across 7 tools
Every tool has a clearly distinct purpose targeting specific resources and actions: retrieving articles by ID, comments, tags, users, stocks, or search. No ambiguity exists as each tool name precisely indicates its function without overlap.
All tools follow a consistent verb_noun pattern using snake_case (e.g., get_item, get_tags, search_items). The naming is highly predictable and readable throughout the set.
With 7 tools, the count is well-scoped for a Qiita article browsing and retrieval server. Each tool earns its place by covering distinct aspects like articles, tags, users, comments, and search.
The tool set provides comprehensive read-only coverage for browsing and retrieving Qiita content, including articles, comments, tags, users, and search. A minor gap exists in write operations (e.g., creating or updating articles), but agents can effectively work with the available tools for querying purposes.
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