Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者による説明(英語の原文)
Connect AI assistants to ITM Platform projects, tasks, budgets, risks, and team workload.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
ITM_API_URL, ITM_COMPANY, ITM_API_KEY必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://api.itmplatform.com/v2/_/mcp/Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"itmplatform": {
"command": "npx",
"args": [
"-y",
"@itm-platform/mcp-server"
],
"env": {
"ITM_API_URL": "your-value",
"ITM_COMPANY": "your-value",
"ITM_API_KEY": "your-value"
}
}
}
}ターミナルでこれを実行します
claude mcp add --transport http itmplatform https://api.itmplatform.com/v2/_/mcp/claude mcp add itmplatform --env ITM_API_URL=your-value --env ITM_COMPANY=your-value --env ITM_API_KEY=your-value -- npx -y @itm-platform/mcp-server動かす前に、空欄の値を入力してください。
プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"itmplatform": {
"url": "https://api.itmplatform.com/v2/_/mcp/"
}
}
}プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"itmplatform": {
"command": "npx",
"args": [
"-y",
"@itm-platform/mcp-server"
],
"env": {
"ITM_API_URL": "your-value",
"ITM_COMPANY": "your-value",
"ITM_API_KEY": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"itmplatform": {
"type": "http",
"url": "https://api.itmplatform.com/v2/_/mcp/"
}
}
}プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"itmplatform": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@itm-platform/mcp-server"
],
"env": {
"ITM_API_URL": "your-value",
"ITM_COMPANY": "your-value",
"ITM_API_KEY": "your-value"
}
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
ChatGPTがつなげるのは、インターネット上のサーバーだけです:
https://api.itmplatform.com/v2/_/mcp/メニューの名前は、プランや時期によって少し違うことがあります。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
ITM_API_URL envITM_COMPANY envITM_API_KEY envこの設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
このサーバーのツール一覧はまだ読み取っていません。エンドポイントは順番にチェックしています。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント itmplatform で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントは順番にチェックしています
まだチェックしていません。エンドポイントをチェックするときにツール一覧を読み取ります
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
どちらでも使えます。パソコンにインストールしても、クラウド版につないでもかまいません。
GitHubリポジトリの最終更新は–、最新バージョン(1.0.22)がレジストリに届いたのは39 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, debuff
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Let coding agents play, test and tune your 2D web game: live state, explained errors, replays, fuzz.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Connect ITM Platform to AI assistants through the Model Context Protocol. The ITM Platform MCP server lets MCP-compatible clients search projects, inspect budgets, summarize portfolio health, create tasks, log risks and issues, and update project details using your ITM Platform permissions.
It works with Claude, VS Code, Cursor, OpenAI Codex, Windsurf, JetBrains AI Assistant, and any other client that supports MCP.
https://api.itmplatform.com/v2/_/mcp/Use the hosted server if your AI client supports remote MCP servers. There is nothing to install: add the URL, sign in with your ITM Platform account, and approve the requested access.
claude mcp add --scope user --transport http itm-platform https://api.itmplatform.com/v2/_/mcp/
For other MCP clients, use this remote URL:
https://api.itmplatform.com/v2/_/mcp/
OAuth is the recommended setup for most users because your AI client never sees your ITM Platform password or API key.
After adding the server, open your AI client, type /mcp where slash commands are supported, select itm-platform, and complete the ITM Platform OAuth login when prompted.
Use the npm package if you prefer to run the server locally, work behind a firewall, or need to connect to a self-hosted ITM Platform instance.
npx @itm-platform/mcp-server
Your MCP client must pass these environment variables to the server:
| Variable | Value |
|---|---|
ITM_API_URL | https://api.itmplatform.com |
ITM_COMPANY | Your company/account slug |
ITM_API_KEY | Your personal API key from ITM Platform |
Example stdio configuration:
{
"mcpServers": { "itm-platform": { "command": "npx", "args": ["@itm-platform/mcp-server"], "env": { "ITM_API_URL": "https://api.itmplatform.com", "ITM_COMPANY": "{your-account}", "ITM_API_KEY": "your-api-key" } } } }
To create an API key, log in to ITM Platform, open My Profile, and generate a key from the API Key section.
After configuring the local server, restart your AI client and use /mcp or the client's MCP server list to confirm itm-platform is connected.
From simple lookups to fully automated cross-system workflows, MCP unlocks progressively more powerful use cases.
Quick lookup -- Ask a question, get an answer:
"What risks are open across my portfolio?"
Multi-step analysis -- The agent chains multiple tools and synthesizes results:
"Review every project ending this quarter. Flag any with budget overruns, open high-impact risks, or task completion below 60%."
Automated bulk actions -- The agent reads, decides, and writes across projects:
"For every project still in Planning status with a start date in the past, update the status to Execution and create a kick-off checklist task assigned to the project manager."
Scheduled intelligence -- An agent runs on a schedule with no human prompt, pulling overdue tasks every Monday and posting a summary to Slack grouped by project manager.
Cross-system orchestration -- Combine ITM Platform's MCP with other MCP servers (GitHub, Slack, Google Calendar, email). When a developer merges a PR, an agent finds the matching ITM Platform task, marks it complete, and if the project hits 100%, drafts a closure summary and emails the program manager.
The MCP server authenticates as you, calls ITM Platform APIs, and returns only the data your ITM Platform account is allowed to access.
The server exposes 47 MCP tools, 6 resources, and 4 prompt templates.
| Tool | What it does |
|---|---|
search_projects | Find projects by name, status, type, or date range |
get_project | Retrieve project details with subcomponent counts and optional budget |
search_services | Find services by name, status, type, or date range |
get_service | Retrieve service details with subcomponent counts and optional budget |
list_project_tasks | List tasks for a project with pagination |
get_task | Retrieve full detail of a single task |
search_tasks | Search tasks across all projects by name, status, assignee, kind, or date range |
get_project_budget | Get budget, actuals, revenue, cost, and margin information |
get_project_purchases | List purchase orders for a project with pagination |
get_project_revenues | List revenue items for a project with pagination |
get_project_risks | List project risks with pagination |
get_project_issues | List project issues with pagination |
get_risk | Retrieve full detail of a single risk, including mitigation and contingency plans |
get_issue | Retrieve full detail of a single issue, including resolution and impact fields |
list_task_progress | List the progress (follow-up) history for a task |
get_task_effort | Get a task's effort breakdown per team member and per professional category; doubles as the task team list |
get_project_progress | Get project progress report: expected, baseline, and actual curves; optionally the full project Seguimiento entries |
list_service_activities | List activities for a service with pagination |
get_service_purchases | List purchase orders for a service with pagination |
get_service_revenues | List revenue items for a service with pagination |
aggregate_portfolio | Group and summarize portfolio data |
query_datamart | Run validated DataMart queries for advanced analysis |
search_users | Find users and team members; returns IsNonLoginUser so non-login users (empty EmailAddress) can be addressed by UserId |
get_user | Retrieve user details |
get_reference_data | Retrieve statuses, types, priorities, and other reference lists |
get_custom_fields | Retrieve the account's custom field definitions for projects, tasks, risks, issues, services, activities, purchases, or revenues |
get_custom_field_options | Retrieve the selectable options of a dropdown custom field |
| Tool | What it does |
|---|---|
create_project | Create a project (Waterfall or Kanban); the project starts with the account default status and the creating user as project manager |
create_task | Add a task, milestone (KindId 1), or summary task (KindId 2); ParentId builds Gantt hierarchy on Waterfall projects; TaskManagers/TaskMembers assign users by username or numeric UserId (the id is the only option for non-login users) |
update_task | Update task fields such as status, dates, kind, and parent; TaskManagers/TaskMembers add assignees by username or numeric UserId (add-only, never removes) |
create_task_progress | Report progress on a task (percentage, assessment, notes) with full side effects |
update_task_progress | Update an existing task progress entry |
update_task_effort | Set the estimated (planned) hours of a task per assigned user; accepted effort and billing data are preserved |
log_time_entry | Log actual worked hours on a task for one user and date; adds to or replaces the day's total, echoing previous and new totals |
create_project_progress | Create a project-level progress (Seguimiento) entry: percentage, assessment, and status description; 100% auto-closes the project |
update_project_progress | Update an existing project progress entry |
create_risk | Log a project risk |
update_risk | Update risk fields such as status, probability, impact, level, and mitigation or contingency plans |
create_issue | Log a project issue with a required issue type and status |
update_issue | Update issue fields such as status, type, and resolution |
update_project | Update project fields such as name, status, dates, and priority |
create_service | Create a service; it starts with the account default status |
update_service | Update service fields such as name, status, dates, and priority |
create_activity | Add an activity to a service (activities form a flat list) |
update_activity | Update activity fields such as status and dates |
bulk_update_task_status | Apply one status to up to 100 tasks of a project in a single call |
bulk_update_activity_status | Apply one status to up to 100 activities of a service in a single call |
Write operations confirm the saved state from the ITM Platform REST API. DataMart-backed search results may take up to 60 seconds to reflect recent writes. Validation failures include the actionable message returned by REST instead of only the HTTP status.
Reads come from DataMart whenever DataMart holds the data (quota-free, portfolio-wide); REST is reserved for data DataMart lacks, single-item authoritative reads (get_task), write readbacks, and reference data. Writes always go to REST. When DataMart gains a dataset, the matching GET tools must migrate to DataMart. Full rule and current routing map: zz_Specifications/progress-history-reads-from-datamart.md.
When the account defines custom fields, each session is enriched with per-account context: the server lists the DataMart customFields keys actually in use in the MCP initialize instructions and in the query_datamart tool description, so agents can read and filter custom field values without prior discovery.
Resources give AI clients read-only context such as DataMart schemas and project calendars. Prompt templates provide guided workflows for common analysis tasks:
| Prompt | What it helps with |
|---|---|
/project_status | Summarize health, tasks, risks, issues, and budget for one project |
/portfolio_overview | Analyze portfolio status, methodology, budget, and delivery patterns |
/team_workload | Review assignments and workload patterns |
/risk_analysis | Assess risk exposure, issues, and budget impact |
The MCP server uses the same identity and permission model as ITM Platform.
| Connection method | Authentication | Best for |
|---|---|---|
| Hosted HTTP | OAuth 2.1 with PKCE | Most users and managed AI clients |
| Local stdio | ITM Platform API key | Local execution, firewalled networks, self-hosted environments |
OAuth sessions use scopes:
| Scope | Allows |
|---|---|
mcp:read | Read-only tools such as search, get, list, aggregate, and query |
mcp:write | Read tools plus create and update tools |
API key sessions use the full permissions of the ITM Platform user who generated the key.
License access:
| License | MCP access |
|---|---|
| Company Admin | Full read and write access |
| Full User | Full read and write access |
| Project Manager | Read and write access scoped to managed projects |
| Team Member | Blocked |
Your AI assistant does not receive your ITM Platform password or API key. Project data is returned to the AI client you choose, so the AI provider's data-handling policy applies to any data it processes.
Use the public docs for client-specific setup:
For any MCP-compatible client, the two connection values are:
| Method | Value
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