Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Beschreibung vom Entwickler (englisches Original)
Shared versioned state for multi-agent AI workflows
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add agenthold -- uvx agenthold --tools standard --db ./agenthold.db --transport stdio --host 127.0.0.1 --port 8417In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"agenthold": {
"type": "stdio",
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto edobusy bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.10.0) kam vor 4 Monaten in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: Spec Driven Development, Remote Desktop Commander, Whisper
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
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.
One routable IPv6 per AI agent, verifiable from the DNS root. Keyless tools need no signup.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
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,
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