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)
Shared versioned state for multi-agent AI workflows
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": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}ターミナルでこれを実行します
claude mcp add agenthold -- uvx agenthold --tools standard --db ./agenthold.db --transport stdio --host 127.0.0.1 --port 8417プロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}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": {
"agenthold": {
"type": "stdio",
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}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7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 edobusy 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(0.10.0)がレジストリに届いたのは4 か月前です。
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Python (uv)も必要です。
同じカテゴリには:Spec Driven Development, Remote Desktop Commander, FactLot
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.
Cited CRE facts and deterministic calculators for agents: rent, CAM, debt sizing, IRR, parcel IDs.
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。
Stop your AI agents from silently overwriting each other.
When two agents update the same value, the second write quietly destroys the first. No error, no exception, just wrong data and a system that keeps running. agenthold is an MCP server that gives agents shared, versioned state with conflict detection built in. Think of it as git for your agents' working memory.
When two agents update the same value at the same time, the second write silently overwrites the first. No exception is raised. The value is wrong. The system keeps running.
Two agents read a $10,000 budget and allocate from it independently. Total committed: $15,000. The budget object never complains. This is a read-modify-write conflict: each agent's write assumes nothing changed since its read.
agenthold solves this with optimistic concurrency control (OCC), the same mechanism Postgres uses in UPDATE ... WHERE version = N and DynamoDB uses in conditional writes.
Every value stored in agenthold has a version number. When an agent writes, it passes the version it read. If the stored version has changed since the read, the write is rejected with a ConflictError that includes the current value. The agent re-reads, recalculates, and retries.
The losing agent detects the conflict, re-reads the real remaining budget ($2,000), and adjusts its allocation. The total committed is always exactly $10,000. Every write is tracked.
OCC is the right fit for agent workflows because:
agenthold connects via MCP (Model Context Protocol), the open standard for tool integration. Any framework that speaks MCP can use agenthold with zero glue code.
| Framework | How to connect |
|---|---|
| Claude Desktop / Claude Code | Built-in: add to mcpServers config |
| Cursor / Continue / Windsurf | Built-in: add to MCP config |
| LangChain / LangGraph | langchain-mcp-adapters |
| CrewAI | Native mcps field on Agent |
| OpenAI Agents SDK | Built-in mcp_servers param |
| Google ADK | Built-in MCP Toolbox |
| AutoGen | autogen_ext.tools.mcp |
| PydanticAI | Native MCP integration |
agenthold is not a framework. It is shared infrastructure that sits underneath your orchestration layer, the same way a database sits underneath your application. Your agents keep their existing tools and logic; agenthold adds the coordination primitive they are missing.
Not using MCP yet? agenthold also works as a Python library you can call directly from any framework. Import
StateStore, call.get()and.set()with version checks, and you have conflict-safe shared state.
graph LR
A1["Agent 1 LangChain, CrewAI, etc."] -->|MCP| S["agenthold MCP Server"] A2["Agent 2 Claude, OpenAI, etc."] -->|MCP| S A3["Agent 3 AutoGen, ADK, etc."] -->|MCP| S S --> DB[("SQLite WAL mode")] DB -->|version 3| S S -->|"conflict! retry"| A2
Every write carries a version number. If the stored version has changed since an agent's read, the write is rejected and the agent retries with current data. This is the same mechanism used by Postgres conditional updates and DynamoDB conditional writes.
pip install agenthold
uv pip install agenthold
{
"mcpServers": { "agenthold": { "command": "agenthold", "args": ["--db", "/path/to/state.db"] } } }
Agents automatically coordinate. No CLAUDE.md, no system prompt changes, no namespace design.
When an agent connects, it sees five self-documenting tools: agenthold_register, agenthold_claim, agenthold_release, agenthold_status, and agenthold_wait. The tool descriptions tell the agent when and how to use each one. Server instructions reinforce the protocol when the MCP client includes them.
agenthold identifies resources by canonical URIs. Tools accept either form:
"src/main.py") — resolves against the workspace named default, or the only configured workspace if exactly one exists."file:// / " for files, "custom:// " for opaque resources.Equivalent inputs (./src/main.py, src\main.py, src//main.py, an absolute path inside the workspace) all canonicalize to the same internal URI, so two agents using different shorthands never fragment the keyspace. Path traversal (..) and dot segments (.) are rejected at the boundary.
On case-insensitive filesystems (Windows and macOS by default), file resources are matched case-insensitively, so src/Main.py and src/main.py resolve to the same resource — two agents can't both claim the same physical file. This follows the running platform; custom:// names are always case-sensitive.
Configure workspaces with --workspace name=path (repeatable). With no flag, agenthold creates a single default workspace at the current working directory. Multi-workspace setups let one agenthold process coordinate across separate codebases.
agenthold exposes five coordination tools by default.
agenthold_registerRegister yourself and receive a unique agent ID. Must be called once before using agenthold_claim or agenthold_release.
{ "name": "editor-agent", "model": "claude-sonnet-4-6" }
{
"status": "registered", "agent_id": "agent-a1b2c3d4", "name": "editor-agent", "registered_at": "2026-03-18T10:00:00+00:00" }
agenthold_claimClaim exclusive access to a resource before modifying it. Requires a registered agent_id.
{ "resource": "intro.md", "agent_id": "agent-a1b2c3d4" }
Claimed (you hold exclusive access):
{ "status": "claimed", "resource": "file://default/intro.md", "version": 1 }
If the resource has a non-trivial prior history (deleted, moved, abandoned, or expired), the response also carries previous_outcome, previous_holder, previous_outcome_at, and a hint describing what the previous holder did. For previous_outcome: "moved", moved_to is the new resource URI.
Busy (another agent is working on this resource):
{
"status": "busy", "resource": "file://default/intro.md", "held_by": "agent-e5f6g7h8", "claimed_at": "2026-03-18T10:00:00+00:00", "hint": "Another agent holds this resource. Work on a different resource, or call agenthold_wait to be notified when it becomes available." }
Already claimed (you already hold this claim, idempotent):
{ "status": "already_claimed", "resource": "file://default/intro.md", "version": 1 }
agenthold_releaseRelease your claim with an explicit outcome describing what you did. The outcome is preserved in the free-state record and shown to the next claimant so they don't act on stale assumptions. Requires a registered agent_id.
{
"resource": "intro.md", "agent_id": "agent-a1b2c3d4", "outcome": "modified" }
{ "status": "released", "resource": "file://default/intro.md", "version": 2, "outcome": "modified" }
Outcomes: released (default — no lifecycle claim), modified (changed in place), created (didn't exist before), deleted (no longer exists at this resource), moved (relocated — also pass moved_to with the new resource).
For renames (mv old new): claim BOTH paths, do the rename on disk, then release the source with outcome: "moved", moved_to: "new" and the destination with outcome: "created".
agenthold_statusCheck whether a resource is available or currently claimed. Does not require registration.
{ "resource": "intro.md" }
Available:
{ "status": "available", "resource": "file://default/intro.md" }
If a previous holder declared a non-trivial outcome (deleted, moved, abandoned, expired), the response also includes previous_outcome, previous_holder, previous_outcome_at, and a hint. For moved, moved_to is the new resource URI.
Claimed:
{
"status": "claimed", "resource": "file://default/intro.md", "held_by": "agent-e5f6g7h8", "agent_name": "editor-agent", "agent_model": "claude-sonnet-4-6", "claimed_at": "2026-03-18T10:00:00+00:00", "version": 3 }
agenthold_waitWait for a claimed resource to become available. Blocks the agent turn until the holder releases, or the timeout expires.
{ "resource": "intro.md", "timeout_seconds": 30 }
Available (resource was released):
{ "status": "available", "resource": "file://default/intro.md", "elapsed_seconds": 2.4 }
When the wait fires on a release with a non-trivial outcome, the response also carries previous_outcome, previous_holder, previous_outcome_at, optional moved_to, and a hint. An agent that was waiting to edit a moved or deleted resource learns *why* the path became available.
Timeout:
{
"status": "timeout", "resource": "file://default/intro.md", "held_by": "writer-2", "elapsed_seconds": 30.2, "hint": "The resource was not released within the timeout. Try working on a different resource, or call agenthold_wait again with a longer timeout." }
For custom coordination protocols, agenthold exposes eight low-level primitives via --tools advanced:
agenthold_get · agenthold_set · agenthold_list · agenthold_history · agenthold_delete · agenthold_watch · agenthold_clear_namespace · agenthold_export
These give agents direct read/write/watch access to the versioned state store with full OCC conflict detection. No server instructions are sent in this mode.
[See the full advanced tools reference →](docs/advanced-tools.md)
The read-modify-write pattern with expected_version is the core of agenthold. Here is the canonical retry loop:
from agenthold.store import StateStore
from agenthold.exceptions import ConflictError
store = StateStore("./state.db")
record = store.get("campaign", "budget") # read once before doing work do_expensive_work() # LLM call,
冒頭だけを表示しています。続きはリポジトリで読めます