Jira Insights (JSM) アセット スキーマを管理するためのモデル コンテキスト プロトコル (MCP) サーバー。
最終更新日: 2025年4月9日
このMCPサーバーは、モデルコンテキストプロトコルを介してJira Insights（JSM）のアセットスキーマと連携するためのツールを提供します。これにより、Jira Insights内のオブジェクトスキーマ、オブジェクトタイプ、およびオブジェクトを管理できます。
Related MCP server: MCP Atlassian
オブジェクト スキーマの管理 (作成、読み取り、更新、削除)
オブジェクト タイプを管理する (作成、読み取り、更新、削除)
オブジェクトの管理（作成、読み取り、更新、削除）
AQL (Atlassian Query Language) を使用してオブジェクトをクエリする
Node.js 20以降
Docker（コンテナ化されたデプロイメント用）
API アクセスを備えた Jira Insights インスタンス
適切な権限を持つ Jira API トークン
リポジトリをクローンします。
git clone https://github.com/aaronsb/jira-insights-mcp.git
cd jira-insights-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 buildDocker イメージをビルドします。
./scripts/build-local.shこの MCP サーバーを、モデル コンテキスト プロトコルをサポートする Claude またはその他の AI アシスタントで使用するには、次のいずれかの方法で MCP 構成に追加します。
プロジェクトをローカルでビルドした場合は、次の構成を使用します。
{
"mcpServers": {
"jira-insights": {
"command": "node",
"args": ["/path/to/jira-insights-mcp/build/index.js"],
"env": {
"JIRA_API_TOKEN": "your-api-token",
"JIRA_EMAIL": "your-email@example.com",
"JIRA_HOST": "https://your-domain.atlassian.net",
"LOG_MODE": "strict"
}
}
}
}Docker イメージを使用する場合 (ほとんどのユーザーに推奨)、次の構成を使用します。
{
"mcpServers": {
"jira-insights": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"-e", "JIRA_API_TOKEN",
"-e", "JIRA_EMAIL",
"-e", "JIRA_HOST",
"ghcr.io/aaronsb/jira-insights-mcp:latest"
],
"env": {
"JIRA_API_TOKEN": "your-api-token",
"JIRA_EMAIL": "your-email@example.com",
"JIRA_HOST": "https://your-domain.atlassian.net"
}
}
}
}この Docker ベースの構成では、GitHub Container Registry から最新のイメージをプルし、必要な環境変数を使用して実行します。
ローカル開発およびテストの場合:
# Build the Docker image
./scripts/build-local.sh
# Run the Docker container
JIRA_API_TOKEN=your_token JIRA_EMAIL=your_email JIRA_HOST=your_host ./scripts/run-local.shCRUD 操作を使用して Jira Insights オブジェクト スキーマを管理します。
{
"operation": "list",
"maxResults": 10
}CRUD 操作を使用して Jira Insights オブジェクト タイプを管理します。
{
"operation": "list",
"schemaId": "1",
"maxResults": 20
}CRUD 操作と AQL クエリを使用して Jira Insights オブジェクトを管理します。
{
"operation": "query",
"aql": "objectType = \"Application\"",
"maxResults": 10
}MCP サーバーは、Jira Insights データにアクセスするためのいくつかのリソースを提供します。
jira-insights://instance/summary - Jira Insights インスタンスに関する高レベルの統計
jira-insights://aql-syntax - Assets Query Language (AQL) 構文の包括的なガイド（例付き）
jira-insights://schemas/all - すべてのスキーマとそのオブジェクトタイプの完全なリスト
jira-insights://schemas/{schemaId}/full - オブジェクトタイプを含む特定のスキーマの完全な定義
jira-insights://schemas/{schemaId}/overview - メタデータと統計を含む特定のスキーマの概要
jira-insights://object-types/{objectTypeId}/overview - 属性や統計情報を含む特定のオブジェクト タイプの概要
Jira Insights MCP の機能性と使いやすさを向上させるために、いくつかの改善に取り組んでいます。
強化されたエラー処理
特定の検証問題に関するより詳細なエラーメッセージ
よくあるエラーの修正方法
ユーザーが問題を修正するのに役立つ操作固有の例
AQLクエリの改善
AQLクエリの検証およびフォーマットユーティリティ
スキーマ固有のサンプルクエリ
クエリの問題に関するエラーメッセージの改善
属性検出の強化
オブジェクトタイプの属性取得の改善
パフォーマンス向上のためのキャッシュ
「expand」パラメータの扱いの改善
オブジェクトテンプレートの生成
オブジェクトの種類に基づいてオブジェクトを作成するためのテンプレート
型固有のプレースホルダー生成
テンプレートの検証ルール
サンプルクエリライブラリ
スキーマ固有のサンプルクエリ
コンテキストに応じたクエリの提案
一般的な操作のクエリテンプレート
改善されたドキュメント
強化されたAQL構文ドキュメント
操作固有のドキュメント
よくあるエラーのシナリオと解決策
計画されている改善の詳細については、以下を参照してください。
TODO.md - すべてのタスクを優先度順に整理した包括的なToDoリスト
IMPLEMENTATION_PLAN.md - 優先度の高い改善のための詳細な実施計画
HANDLER_IMPROVEMENTS.md - 各ハンドラーファイルに必要な特定の変更
IMPROVEMENT_SUMMARY.md - 計画されている改善の簡潔な概要
docs/API_MIGRATION_TODO.md - API 移行のステータスと計画されている改善
npm run build : TypeScriptコードをビルドする
npm run lint : ESLint を実行する
npm run lint:fix : 自動修正付きで ESLint を実行する
npm run test : テストを実行する
npm run watch : 変更を監視して再構築する
npm run generate-diagrams : TypeScript依存関係図を生成する
./scripts/build-local.sh : Dockerイメージをビルドする
./scripts/run-local.sh : Dockerコンテナを実行する
AQLクエリ検証エラー
スペースを含む値は引用符で囲んでください: Name = "John Doe"
論理演算子には大文字を使用します: AND 、 OR ( and 、 orない)
スキーマにオブジェクトタイプと属性が存在することを確認する
オブジェクト型属性の問題
「属性」で「展開」パラメータを使用する場合は、オブジェクトタイプが存在することを確認してください。
属性を表示する権限があることを確認してください
API接続の問題
Jira APIトークンに必要な権限があることを確認する
JiraホストURLが正しいことを確認してください
ネットワークが Jira API への接続を許可していることを確認する
マサチューセッツ工科大学
Manage Jira Insights objects with CRUD operations and AQL queries
| Name | Required | Description | Default |
|---|---|---|---|
| aql | No | AQL query string. Required for query operation. IMPORTANT: For comprehensive AQL documentation, refer to the "jira-insights://aql-syntax" resource using the access_mcp_resource tool. This resource contains detailed syntax guides, examples, and best practices. Guide to Constructing Better Jira Insight AQL Queries: Understanding AQL Fundamentals: - Object Type Case Sensitivity: Use exact case matching for object type names (e.g., ObjectType = "Supported laptops" not objectType = "Supported laptops"). - String Values in Quotes: Always enclose string values in double quotes, especially values containing spaces (e.g., Name = "MacBook Pro" not Name = MacBook Pro). - Attribute References: Reference attributes directly by their name, not by a derived field name (e.g., use Name not name). - LIKE Operator Usage: Use the LIKE operator for partial string matching, but be aware it may be case-sensitive. Effective Query Construction: - Start Simple: Begin with the most basic query to validate object existence before adding complex filters: ObjectType = "Supported laptops" - Examine Response Objects: Study the first responses to understand available attribute names and formats before using them in filters. - Keyword Strategy: When searching for specific items, try multiple potential keywords (e.g., "ThinkPad", "Lenovo", "Carbon") rather than just exclusion logic. - Incremental Complexity: Add filter conditions incrementally, testing after each addition rather than constructing complex queries in one step. Managing Complex Queries: - AND/OR Operators: Structure complex conditions carefully with proper parentheses: ObjectType = "Supported laptops" AND (Name LIKE "ThinkPad" OR Name LIKE "Lenovo") - NOT Operators: Use NOT sparingly and with proper syntax: ObjectType = "Supported laptops" AND NOT Name LIKE "MacBook" - Reference Object Queries: For filtering on related objects, use their object key as a reference: ObjectType = "Supported laptops" AND Manufacturer = "PPL-231" - Pagination Awareness: For large result sets, utilize the startAt and maxResults parameters to get complete data. | |
| attributes | No | Attributes of the object as key-value pairs. Optional for create/update. | |
| expand | No | Optional fields to include in the response | |
| includeAttributes | No | Should the objects attributes be included in the response. If this parameter is false only the information on the object will be returned and the object attributes will not be present. | |
| includeAttributesDeep | No | How many levels of attributes should be included. E.g. consider an object A that has a reference to object B that has a reference to object C. If object A is included in the response and includeAttributesDeep=1 object A's reference to object B will be included in the attributes of object A but object B's reference to object C will not be included. However if the includeAttributesDeep=2 then object B's reference to object C will be included in object B's attributes. | |
| includeExtendedInfo | No | Include information about open Jira issues. Should each object have information if open tickets are connected to the object? | |
| includeTypeAttributes | No | Should the response include the object type attribute definition for each attribute that is returned with the objects. | |
| maxResults | No | Maximum number of objects to return. Used for list and query operations. Can also use snake_case "max_results". | |
| name | No | Name of the object. Required for create operation, optional for update. | |
| objectId | No | The ID of the object. Required for get, update, and delete operations. Can also use snake_case "object_id". | |
| objectTypeId | No | The ID of the object type. Required for create operation. Can also use snake_case "object_type_id". | |
| operation | Yes | Operation to perform on the object | |
| resolveAttributeNames | No | Replace attribute IDs (attr_xxx) with actual attribute names in the response. This provides more meaningful attribute names for better readability. | |
| schemaId | No | The ID of the schema to use for enhanced validation. When provided, the query will be validated against the schema structure, providing better error messages and suggestions. | |
| simplifiedResponse | No | Return a simplified response with only essential key-value pairs, excluding detailed metadata, references, and type definitions. Useful for reducing response size and improving readability. | |
| startAt | No | Index of the first object to return (0-based). Used for list and query operations. Can also use snake_case "start_at". |
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 mentions 'CRUD operations and AQL queries' but lacks details on permissions, side effects, rate limits, or response formats. For a tool with 16 parameters and complex operations like delete/update, this is insufficient—it doesn't explain what 'manage' entails beyond high-level operations.
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 overly concise to the point of under-specification—it's a single sentence that fails to convey necessary details for such a complex tool. It lacks front-loaded critical information and doesn't structure guidance effectively, making it inefficient despite its brevity.
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 (16 parameters, no annotations, no output schema), the description is incomplete. It doesn't address behavioral aspects, usage context, or output expectations, leaving significant gaps. For a multi-operation tool managing objects, more comprehensive guidance is needed to support effective agent 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 adds minimal parameter semantics beyond the input schema, which has 100% coverage. It implies parameters relate to CRUD and AQL operations but doesn't elaborate on specific usage or interactions. Since schema coverage is high, the baseline is 3, but the description doesn't compensate with additional insights like parameter dependencies or examples.
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: 'Manage Jira Insights objects with CRUD operations and AQL queries.' It specifies the resource (Jira Insights objects) and the operations (CRUD + AQL queries). However, it doesn't explicitly differentiate from sibling tools like 'manage_jira_insight_object_type' or 'manage_jira_insight_schema,' which likely manage different resources.
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 its siblings or alternatives. It mentions CRUD operations and AQL queries but doesn't specify scenarios, prerequisites, or exclusions. For example, it doesn't clarify if this is for basic object management while siblings handle types/schemas, leaving usage context implied at best.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage Jira Insights object types with CRUD operations
| Name | Required | Description | Default |
|---|---|---|---|
| description | No | Description of the object type. Optional for create/update. | |
| expand | No | Optional fields to include in the response | |
| icon | No | Icon for the object type. Optional for create/update. | |
| maxResults | No | Maximum number of object types to return. Used for list operation. Can also use snake_case "max_results". | |
| name | No | Name of the object type. Required for create operation, optional for update. | |
| objectTypeId | No | The ID of the object type. Required for get, update, and delete operations. Can also use snake_case "object_type_id". | |
| operation | Yes | Operation to perform on the object type | |
| schemaId | No | The ID of the schema. Required for create operation. Can also use snake_case "schema_id". | |
| startAt | No | Index of the first object type to return (0-based). Used for list operation. Can also use snake_case "start_at". |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states 'CRUD operations' without detailing permissions, side effects, rate limits, or response behavior. It lacks critical information for a mutation-capable tool.
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 without unnecessary words. It's appropriately sized for the tool's complexity.
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 9 parameters, no annotations, and no output schema, the description is insufficient. It doesn't explain return values, error handling, or behavioral nuances needed for safe and 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 parameters are well-documented in the schema. The description adds no additional parameter semantics beyond the generic 'CRUD operations', which aligns with 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 states the tool performs CRUD operations on Jira Insights object types, which is a clear purpose. However, it doesn't differentiate from sibling tools like 'manage_jira_insight_object' or 'manage_jira_insight_schema', leaving ambiguity about scope boundaries.
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 its siblings or alternatives. The description mentions CRUD operations but doesn't specify contexts, prerequisites, or exclusions for usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Manage Jira Insights object schemas with CRUD operations
| Name | Required | Description | Default |
|---|---|---|---|
| description | No | Description of the schema. Optional for create/update. | |
| expand | No | Optional fields to include in the response | |
| maxResults | No | Maximum number of schemas to return. Used for list operation. Can also use snake_case "max_results". | |
| name | No | Name of the schema. Required for create operation, optional for update. | |
| operation | Yes | Operation to perform on the schema | |
| schemaId | No | The ID of the schema. Required for get, update, and delete operations. Can also use snake_case "schema_id". | |
| startAt | No | Index of the first schema to return (0-based). Used for list operation. Can also use snake_case "start_at". |
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 but only states 'manage with CRUD operations.' It doesn't describe authentication requirements, rate limits, error conditions, what 'delete' actually destroys, or response formats. For a multi-operation tool with mutation capabilities, 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, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded with the core purpose, though it could benefit from more detail given the tool's complexity.
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 complex tool with 7 parameters supporting 5 different operations (including destructive ones like delete) and no output schema or annotations, the description is inadequate. It doesn't explain return values, error handling, or operational constraints, leaving the agent with insufficient context to use the tool 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?
Schema description coverage is 100%, so the schema already documents all 7 parameters thoroughly. The description adds no parameter-specific information beyond the generic 'CRUD operations' mention, which doesn't provide additional semantic context about individual parameters or their relationships.
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 states the tool manages Jira Insights object schemas with CRUD operations, which provides a general purpose but lacks specificity about what 'manage' entails. It doesn't distinguish this schema management tool from its sibling object and object type management tools, leaving the scope vague.
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 about when to use this tool versus its siblings (manage_jira_insight_object and manage_jira_insight_object_type). The description mentions CRUD operations but doesn't specify contexts, prerequisites, or exclusions for choosing this schema management tool over alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0manage_jira_insight_objectmanage_jira_insight_object_typemanage_jira_insight_schemaEach tool has a clearly distinct purpose targeting different Jira Insights components: objects, object types, and schemas. The descriptions specify unique domains (objects, object types, schemas) with no overlap in functionality, making it easy for an agent to select the correct tool.
All tool names follow a consistent verb_noun pattern with 'manage_jira_insight_' prefix followed by the specific component (object, object_type, schema). This predictable naming convention enhances readability and usability across the tool set.
With only 3 tools, the count feels thin for a server named 'Jira Insights MCP', which might imply broader functionality. However, it covers core management areas adequately, though it could benefit from additional tools for querying or reporting to be more comprehensive.
The tools provide CRUD operations for key Jira Insights components (objects, types, schemas), covering essential management tasks. A minor gap exists in lacking dedicated query or analysis tools beyond AQL mentioned in one description, but core workflows are well-supported.
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