Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Descripción del creador (original en inglés)
Shared versioned state for multi-agent AI workflows
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Ejecuta esto en tu terminal
claude mcp add agenthold -- uvx agenthold --tools standard --db ./agenthold.db --transport stdio --host 127.0.0.1 --port 8417Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"agenthold": {
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"agenthold": {
"type": "stdio",
"command": "uvx",
"args": [
"agenthold",
"--tools",
"standard",
"--db",
"./agenthold.db",
"--transport",
"stdio",
"--host",
"127.0.0.1",
"--port",
"8417"
]
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
Esta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 6 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub edobusy, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.10.0) llegó al registro hace 4 meses.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Spec Driven Development, Remote Desktop Commander, Toggl 2.0
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
Toggl 2.0 MCP server for tasks, projects, time entries, and workspace operations.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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,
Solo se muestra el principio; lee el resto en el repo