,APEX MCP Server
APEX MCPサーバー
APEX用モデルコンテキストプロトコル(MCP)サーバー - 欧州企業向け規制インテリジェンスプラットフォーム。
インストール
npmから(推奨)
npm install -g @apex-dev/mcp-serverソースから
git clone https://github.com/apex-dev/mcp-server.git
cd mcp-server
npm install
npm run buildRelated MCP server: EU AI Act Compliance MCP Server
設定
MCP設定ファイルに追加してください:
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"apex": {
"command": "npx",
"args": ["-y", "@apex-dev/mcp-server"],
"env": {
"APEX_API_KEY": "your_api_key_here",
"APEX_API_BASE": "https://api.apex.dev"
}
}
}
}Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"apex": {
"command": "npx",
"args": ["-y", "@apex-dev/mcp-server"],
"env": {
"APEX_API_KEY": "your_api_key_here"
}
}
}
}Cline (VS Code拡張機能 - 設定で構成):
{
"mcpServers": {
"apex": {
"command": "npx",
"args": ["-y", "@apex-dev/mcp-server"],
"env": {
"APEX_API_KEY": "your_api_key_here"
}
}
}
}利用可能なツール
apex_search
欧州のソース(GDPR、ISO27001、AI法など)から規制関連出版物を検索します。
パラメータ:
query(string): 検索語句topics(array): フィルタリングするトピックIDfrom(string): 開始日 (ISO 8601)to(string): 終了日 (ISO 8601)limit(number): 最大結果数
例: 「過去30日間のGDPRおよびAI規制を検索」
apex_create_topic
新しい監視トピックを作成します。
パラメータ:
name(string): トピック名keywords(array): 監視するキーワード
例: 「キーワード:人工知能、機械学習、AI法 を含む AI_REGULATION というトピックを作成」
apex_list_topics
利用可能なすべての監視トピックを一覧表示します。
apex_create_follow
通知付きの監視を設定します。
パラメータ:
topics(array): フォローするトピックIDfrequency(string): "realtime"(リアルタイム)、"daily"(毎日)、または "weekly"(毎週)channels(array): ["email", "slack", "webhook"]
apex_generate_brief
コンプライアンス概要を生成します。
パラメータ:
period(string): "daily"、"weekly"、または "custom"topics(array): 含めるトピックIDformat(string): "markdown"、"json"、または "html"
ユースケース
欧州のTPE/PME(小規模・中堅企業)向け
RGPDコンプライアンスの更新を監視
ISO27001認証要件を追跡
AI法の施行に関する最新情報を把握
開発者向け
コンプライアンス対応アプリケーション構築時の規制コンテキストを取得
CI/CDパイプラインでのコンプライアンス監視を自動化
ステークホルダー向けの規制概要を生成
AIエージェント向け
リアルタイムの規制インテリジェンスにアクセス
コンプライアンス監視ワークフローを作成
構造化されたコンプライアンスレポートを生成
API統合
直接のAPI統合(MCPなし)については、以下を参照してください:https://docs.apex.dev
開発
# Install dependencies
npm install
# Build
npm run build
# Run in development
npm run dev
# Test with MCP inspector
npx @modelcontextprotocol/inspector node dist/index.jsライセンス
MIT © 2026 APEX
Available Tools
5 toolsapex_create_followC
Create a monitoring follow with notifications for regulatory updates
| Name | Required | Description | Default |
|---|---|---|---|
| topics | Yes | Topic IDs to follow | |
| frequency | No | Notification frequency | |
| channels | No | Notification channels |
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 tool creates a follow with notifications, implying a write operation, but doesn't cover critical aspects like permissions required, whether the follow is reversible, rate limits, or what the response looks like. For a creation tool with zero annotation coverage, this leaves significant gaps in understanding its 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, efficient sentence that front-loads the core action and purpose without any wasted words. It's appropriately sized for the tool's complexity, 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 complexity (a creation operation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what a 'monitoring follow' entails, how notifications work, or what happens after creation. For a tool that likely involves persistent monitoring and notifications, 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?
Schema description coverage is 100%, so the schema already documents all parameters (topics, frequency, channels) with descriptions and enums. The description adds no additional meaning beyond what's in the schema, such as explaining how topics relate to regulatory updates or the implications of frequency choices. 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 action ('Create a monitoring follow') and the purpose ('with notifications for regulatory updates'), which distinguishes it from sibling tools like apex_create_topic or apex_list_topics. However, it doesn't explicitly differentiate from apex_generate_brief or apex_search, which might also involve monitoring or regulatory content, so it's not fully sibling-distinct.
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, such as needing existing topics from apex_list_topics, or when to choose this over apex_generate_brief for regulatory updates. Without any context on usage scenarios or exclusions, the agent lacks direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
apex_create_topicC
Create a new monitoring topic for regulatory intelligence tracking
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Topic name (e.g., "AI_REGULATION") | |
| keywords | Yes | Keywords to monitor |
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 tool creates something, implying a write operation, but doesn't cover critical aspects like permissions needed, whether creation is idempotent, rate limits, or what happens on success/failure. This leaves significant gaps for an agent to understand 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 unnecessary words. It is front-loaded and efficiently conveys the essential information, making it highly concise and well-structured.
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 as a creation operation with no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns, error conditions, or behavioral traits like side effects, which are crucial for an agent to use it correctly in context.
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 both parameters ('name' and 'keywords') adequately. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or constraints, meeting the baseline for high schema 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 action ('Create') and resource ('new monitoring topic for regulatory intelligence tracking'), providing a specific purpose. However, it doesn't explicitly differentiate from sibling tools like 'apex_create_follow' or 'apex_list_topics', 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 like 'apex_list_topics' or 'apex_search'. It lacks context about prerequisites, such as whether topics must be unique or if there are limits, and doesn't mention when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
apex_generate_briefC
Generate a compliance brief summarizing recent regulatory publications
| Name | Required | Description | Default |
|---|---|---|---|
| period | No | Brief period | |
| topics | No | Topic IDs to include | |
| format | No | Output format |
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 tool 'generates' a brief, implying a read-only or generative operation, but doesn't specify if it requires authentication, has rate limits, affects data, or details the output structure. 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 unnecessary words. It's front-loaded and appropriately sized, 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 complexity (generating summaries with three parameters) and lack of annotations and output schema, the description is incomplete. It doesn't cover behavioral aspects like permissions or output format details, leaving gaps that could hinder correct tool invocation by an agent.
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, with clear enum values and descriptions for all three parameters. The description doesn't add any semantic details beyond what the schema provides, such as explaining 'custom' period usage or topic ID sources. Baseline 3 is appropriate since 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 ('generate') and resource ('compliance brief'), specifying it summarizes recent regulatory publications. However, it doesn't explicitly differentiate from sibling tools like apex_search or apex_list_topics, which might also involve regulatory content but serve different functions.
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, exclusions, or compare it to sibling tools like apex_search for broader queries or apex_list_topics for topic management, 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.
apex_list_topicsC
List all available monitoring topics
| Name | Required | Description | Default |
|---|---|---|---|
| active | No | Filter by active status |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure. It states this is a list operation but doesn't mention whether it's paginated, what format the output takes, or any rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency.
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's appropriately sized for a simple list operation and front-loads the essential information.
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 no annotations and no output schema, the description is insufficiently complete. It doesn't explain what 'monitoring topics' are, what the output format looks like, or any behavioral constraints. Given the lack of structured data, the description should provide more context.
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, with the single parameter 'active' documented as filtering by active status. The description adds no additional parameter information beyond what the schema provides, so it meets the baseline score for high schema 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 ('List') and resource ('all available monitoring topics'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'apex_search', which might also list topics with different filtering capabilities, 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.
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 'apex_search' or 'apex_create_topic'. It mentions no prerequisites, exclusions, or specific contexts, leaving the agent to infer usage from 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.
apex_searchC
Search regulatory publications and compliance updates from European sources (RGPD, ISO27001, etc.)
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Search terms (e.g., "RGPD artificial intelligence") | |
| topics | No | Topic IDs to filter by | |
| from | No | Start date (ISO 8601 format) | |
| to | No | End date (ISO 8601 format) | |
| limit | No | Maximum results (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 searching but doesn't disclose behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or what the search results look like (e.g., format, pagination). 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 core purpose ('Search regulatory publications...') and includes relevant examples. Every word earns its place, with no wasted text or redundancy.
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 search tool with 5 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral aspects (e.g., read-only nature, result format) and doesn't compensate for the absence of structured output information, making it inadequate for full agent understanding.
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 the schema already documents all 5 parameters (query, topics, from, to, limit) with clear descriptions. The description adds no additional meaning beyond what the schema provides, such as explaining how topics relate to European sources or default behaviors. 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 action ('Search') and the resource ('regulatory publications and compliance updates from European sources'), with specific examples like RGPD and ISO27001. It distinguishes this as a search tool, but doesn't explicitly differentiate from sibling tools like apex_generate_brief or apex_list_topics, which might also involve regulatory content.
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 apex_list_topics (which might list topics without searching) or apex_generate_brief (which might summarize content), leaving the agent to infer usage from 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.
5 tool updates
v0.1.0- First observed
apex_create_follow - First observed
apex_create_topic - First observed
apex_generate_brief - First observed
apex_list_topics - First observed
apex_search
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: apex_create_follow handles notification setups, apex_create_topic manages topic creation, apex_generate_brief produces summaries, apex_list_topics retrieves topic lists, and apex_search performs regulatory searches. There is no overlap in functionality, making tool selection straightforward for an agent.
All tools follow a consistent 'apex_verb_noun' pattern with snake_case, such as apex_create_follow and apex_list_topics. This uniformity enhances readability and predictability across the toolset, with no deviations in naming conventions.
With 5 tools, the server is well-scoped for regulatory monitoring and compliance intelligence. Each tool serves a specific function (creation, listing, searching, briefing) without redundancy, making the count appropriate and manageable for the domain.
The toolset covers key operations like creating and listing topics, generating briefs, and searching publications, which supports core workflows. A minor gap exists in update or delete functionality for topics or follows, but agents can likely work around this for basic monitoring tasks.
Maintenance
Related MCP Connectors
EU regulations (GDPR, DORA, NIS2, AI Act, etc.) via Ansvar Gateway. Cited, OAuth + paid.
EU compliance corpus across 8 frameworks (NIS2, DORA, AI Act, ISO 27001 + more) via MCP.
EU regulatory compliance data: 17 regulations, deadlines, enforcement actions. EU-hosted.
Verified, tier-0 regulatory data for AI across 850+ official sources and 50+ jurisdictions.
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