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)
Repository MCP adapter for company-scoped workflow candidates and conditional API discovery.
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。
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。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"agenticorg": {
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}ターミナルでこれを実行します
claude mcp add agenticorg -- npx -y agenticorg-mcp-serverプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"agenticorg": {
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}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": {
"agenticorg": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"agenticorg-mcp-server"
]
}
}
}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。
これはパソコンで動くサーバーですが、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。ほかのアプリを選んでください。
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。
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。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
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 mishrasanjeev 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
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
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。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(5.0.0)がレジストリに届いたのは28 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。パソコンにNode.jsも必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, TF Rooms
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.
Live room availability, rates and stay quotes for 12 New Leaf motels in Twin Falls, Idaho.
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。
AgenticOrg is an enterprise AI agent platform for building, running, and governing agent workflows across finance, HR, marketing, operations, back office, communications, and bounded agentic-commerce use cases. The platform is source-available under the Orchestrum Personal Use License 1.0: only individuals' personal use is free, and any organisation needs a signed agreement with Orchestrum Technologies LLP; the SDKs and MCP server are Apache-2.0 open source (see Licence).
Ownership: AgenticOrg is owned by Orchestrum Technologies LLP.
Inventor / Owner: Sanjeev Kumar
Contact: sanjeev@orchestrum.in | mishra.sanjeev@gmail.com
Website demo and trial lead notifications default to sanjeev@orchestrum.in. Self-hosted operators can select their own single marketing inbox with AGENTICORG_DEMO_NOTIFY_TO. This does not redirect requester confirmations, workspace notifications, or account-recovery email, and does not replace SMTP setup.
See the canonical ownership and contact statement and NOTICE.
Website | Application | Playground | User manual | Technical documentation | Current product status | Security policy
Start with a measurable pilot: bank service cases, fintech/API integrations, or merchant and external-buyer workflows. The visual rollout checklist explains source setup, review, external confirmation and expansion. Discuss your task and systems at sanjeev@orchestrum.in; do not send credentials or customer data in a public enquiry.
The AgenticOrg platform is source-available under the [Orchestrum Personal Use License 1.0](LICENSE). Only an individual using it for their own personal purposes is free. Every organisation (companies, firms, sole proprietors' businesses, charities, schools, universities, research bodies and government) needs prior written permission in a signed agreement with Orchestrum Technologies LLP, for any use: evaluation, testing, pilots, internal use, hosting, resale or embedding, paid or free.
The AgenticOrg SDKs (`sdk/`, `sdk-ts/`) and the MCP server (`mcp-server/`) are open source under the Apache License 2.0, free for any use including commercial.
| Directory | Licence |
|---|---|
sdk/ (Python SDK) | Apache License 2.0: open source, free for any use including commercial |
sdk-ts/ (TypeScript SDK) | Apache License 2.0: open source, free for any use including commercial |
mcp-server/ (MCP server) | Apache License 2.0: open source, free for any use including commercial |
tests/fixtures/ucp/, core/commerce/acp/schemas/ (vendored protocol schemas) | Apache License 2.0 (third-party, unchanged) |
Everything else: the AgenticOrg platform (api/, core/, auth/, connectors/, ui/ and the website, workers, docs/, scripts/, migrations/, tests) | Orchestrum Personal Use License 1.0: individuals' personal use only; any organisation needs a signed agreement with Orchestrum Technologies LLP |
Live product totals and the deployed product version are published by the public product facts endpoint:
GET https://app.agenticorg.ai/api/v1/product-facts
The response contains version, agent_count, connector_count, and tool_count. Do not copy those values into documentation, page copy, or tests: they are computed from runtime registries and can change independently of a documentation release. The version declared for source builds is in pyproject.toml.
Billing limits and list prices come from core/billing/catalog.py. Production deployment behavior comes from scripts/deploy_cloud_run.sh.
New agents default to gemini-3.5-flash-lite; explicitly selected models remain unchanged. Save your Google or other provider key in the protected AI credential settings. Model selection, fallback and company scope remain configurable. For this model, Agent Configuration > Gemini thinking offers an optional medium profile for multi-step reasoning. Existing agents and generic calls keep the provider default; no global flag or default is changed. The API equivalent is llm.thinking_level="medium"; set it to null to restore the provider default. Both runtime clients honor explicit profiles. Thinking is billed as output tokens; budget for its additional token use and response time within existing limits. It is not a correctness guarantee. Older model settings and all feature flags remain unchanged. See reasoning acceptance.
The Channels dashboard connects your own WhatsApp Cloud API, Meta Messenger, Telegram, Viber, inbound Mailgun email or signed gateway to an agent or workflow. Credentials are encrypted, callbacks are authenticated, unlinked messages require review, and private sender links delegate only your current permissions. Existing Twilio voice/call setup and remote MCP tool discovery remain separate integrations. Native channel replies default to optional status notices. Telegram agent connections can opt into bounded final-answer replies for the linked private sender under Channels > Reply content. Traces and tool-call records stay in AgenticOrg; approvals, sender authorization and tenant controls still apply. The encrypted intake carries the authenticated sender identity across services; older receipts without that proof remain withheld, even if the agent completed. For tool-free Telegram agents without traffic splits in this opt-in mode, follow-ups may use up to four recent, confirmed question/answer pairs from the same linked private sender and agent/company scope, within 30 minutes. This is bounded text context, not durable memory or permission to repeat actions. Hindi and other Unicode model input remains readable before privacy scanning; existing redaction still applies. With AGENTICORG_PII_HINDI_GRAMMAR_ENABLED=true (default off), targeted Hindi grammar checks distinguish referential name/colour questions from named values. This is not a general-purpose Hindi entity-recognition model; quoted names, unknown words and structured identifiers retain privacy scanning.
Follow the channel account and workflow guide for account creation, callback registration, sender linking and verification. Local wire-contract tests are not proof of real provider-account delivery. Reuse an existing Telegram connection for an already connected bot; a second connection must not overwrite its webhook. Change its destination through Save settings only when authorized and no tasks are queued or running. Verify real model reasoning separately from transport-only workflows, and do not claim a combined Telegram-to-Gemini flow unless one delivery proves both.
Acceptance checks validate the actual answer as well as the terminal status. A completed, high-confidence model run can still be wrong; compare numeric results independently and preserve PII protections while diagnosing it. See the bounded production acceptance runbook.
The production platform currently includes governed agent/workflow execution, document ingestion with scanned-document OCR, signed Twilio voice with provider-managed STT/TTS, tenant-scoped browser RPA, Python and TypeScript SDKs, MCP/A2A surfaces, and the bounded Shopify-to-OACP commerce runtime. See the current product status for the exact shipped, configuration-dependent, and not-shipped boundaries.
External actions remain explicit. A voice provider, connector, browser script, buyer channel, payment rail, merchant system, or POS path is usable only when the target tenant has the required credentials, scopes, configuration, and provider approval.
The repository includes a tenant-gated business onboarding case workflow with read-only provider investigation, a cited memo, deterministic policy scoring, screening dispositions, human review, and an auditable hand-off. Provider calls are refused unless the active role agent, registered tools, exact local case purpose, and delegated grant all authorize the call. This case-specific check is strict even if general tool enforcement is in off or warn mode.
AgenticOrg pins grantex==0.7.1 and calls its enforcement check with the grant token, connector, tool and any numeric amount. It does not pass a case id or case purpose, so a token's case purpose and per-case caps are not checked on this path. The role's case_purposes list is a local AgenticOrg control, and pooled grants are not bound to one case. Decision and analyst actions still require a signed-in human; API keys, agent tokens, and MCP tools cannot act as that human. The case runtime is off for a tenant until enabled and configured. This source description is not a claim that a particular hosted deployment has enabled the workflow. See the case lifecycle and setup, grant-enforcement runbook, and decision requests.
Voice, email, OCR, and browser RPA can be exercised together before release with the Docker-backed local multichannel simulation. It uses fresh PostgreSQL, local Mailpit delivery, real Tesseract, and optional real Playwright Chromium while keeping paid calls and production mutations off.
Knowledge upload status distinguishes extraction from searchable indexing. With opt-in upload recovery, transient native embedding failures retry on the existing worker; the previous searchable copy remains until replacement succeeds. Malformed PDF/Office files are refused before replacement. See Knowledge and OCR for status meanings, citations and recovery limits. For a reasoning-only agent, disable suggested tools and leave tool/connector selection empty; this does not bypass tenant budgets. Provider charges and quotas still apply. Use structured output for conf
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