mcpbeat Sign in

ddflow MCP Server

local only

ddflow runs on your own machine — the client starts it, so there is no endpoint to ping. 1 944 installs a week from pypi. Last commit 25 Oct 2026.

Work-queue kernel for AI coding agents: dependencies, worktree isolation, quality gates, recovery

Installs per day peak 3 450 · avg 430 · +19% w/w
a month agotoday
1 944
Installs / week
pypi · ddflow-mcp
0
Stars
0 open issues
25 Oct 2026
Last commit
from GitHub
MIT
License
Python

What the code does

We read the source, 1 d ago · rules 995398eba69f

Capabilities

What this server is able to do. For an MCP server this is often the job itself — a terminal server runs commands because that is what it is for. Listed so you know what you are plugging in, not as an accusation.

    if Path("/.dockerenv").exists() or Path("/run/.containerenv").exists():
    db = os.path.join(root, f"probe-{mode}.db")
    return subprocess.run(["git", "-C", str(cwd), *a], capture_output=True, text=True)
            body = marshal.loads(payload)  # nosec B302
        shell=True,  # nosec B602 B604 -- the operator's configured shell line

Is this your server and something here is wrong? Tell us — corrections are free and do not require a plan.

This code can reach further than it looks

We found places where it runs commands, builds paths or queries from values it is given. None of that is a flaw by itself — it becomes one when the code changes, and code changes quietly between releases. We re-read it on every one.

Three servers free · no card

Connect this server

This server runs on your own machine — install it with the package manager and the client starts it for you. Package name taken from the official registry entry.

run in your terminal
claude mcp add ddflow-mcp -- uvx ddflow-mcp
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "ddflow-mcp": {
      "command": "uvx",
      "args": [
        "ddflow-mcp"
      ]
    }
  }
}
~/.codex/config.toml
[mcp_servers.ddflow-mcp]
command = "uvx"
args = ["ddflow-mcp"]
.cursor/mcp.json
{
  "mcpServers": {
    "ddflow-mcp": {
      "command": "uvx",
      "args": [
        "ddflow-mcp"
      ]
    }
  }
}
.vscode/mcp.json
{
  "servers": {
    "ddflow-mcp": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ddflow-mcp"
      ]
    }
  }
}

Optional settings from the registry entry, left out of the block above: DDFLOW_REPO (Repository root ddflow manages. Defaults to the client's working directory, resolved to the primary checkout even when called from inside a git worktree), DDFLOW_AGENT (Stable identity for this agent. Shards the event log so concurrent agents never write the same file. Defaults to host plus the git worktree's name, so every process in one worktree agrees and two parallel agents differ. A harness running SEVERAL agents inside one worktree must set this, or their work merges into a single identity).

Alternatives to ddflow

same job, measured the same way
MCP Task Orchestrator
by jpicklyk

Server-enforced workflow discipline for AI agents: work items, dependency graphs, quality gates

local only
K-Work Trust
by hycore220

Korean business record validation and workflow safety gates for AI agents.

3 tools answering
git-a2a
by neprel

Git module dependencies and owning-agent routing for coding agents

34 installs/wk local only
L
LicenseGate
by computersmarts1

Open-source licence risk checks for AI coding agents and dependency trees.

1 tools answering
Agent Core
by kinbinghua-lgtm

Deterministic computation tools for AI agents. Zero dependencies, no network, read-only.

22 installs/wk local only
Agent Enhancer Utilities
by liberated

Workflow planning, recovery checkpoints, coordination, fixtures, and compatibility tools for agents.

6 tools answering
Cortex
by filippopilo

Patent-pending semantic memory for AI agents: quality-gated writes, conflict tracking. Free trial.

7 tools answering
Syke
by khalomsky

AI code impact analysis — dependency graphs, cascade detection, and build gates for AI agents

99 installs/wk local only

ddflow — questions

Answers built from our own checks of this server.

Why is there no uptime for ddflow?
ddflow runs on your own machine over stdio — there is no network address to reach, so uptime cannot be measured for it by anyone. What can be measured is adoption: the pypi package ddflow-mcp was installed 1 944 times last week.
How do I connect ddflow?
Copy the ready config from this page. We generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each in the form that client actually reads. It runs locally, so the command pulls ddflow-mcp straight from pypi; nothing to host, nothing to sign up for.
How many people use ddflow?
The pypi package ddflow-mcp was installed 1 944 times in the last week. Week over week that is +19%. We show installs rather than GitHub stars on purpose: a star is a bookmark, an install is someone actually running it.
Is ddflow open source?
Yes — it is published under the MIT licence, written in Python and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.