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Coordinate multiple AI agents safely on the same codebase in real time.
This MCP tool appears to support multi-agent coordination on the same codebase, with code-execution capability and real-time coordination via a WebSocket-based mechanism. It declares no required secrets or fixed remote endpoints, and the source is open for review, but documentation is sparse and adoption is low, so the overall posture is caution rather than high risk.
The materials explicitly state that no keys or environment variables are required, and there is no request for API tokens, account credentials, or other sensitive authentication data; based on the provided facts, credential exposure appears low.
The description says it is a WebSocket-based MCP server for real-time file locking and coordination state, which implies network communication capability; however, no fixed remote host is declared, and the available materials do not show data being exfiltrated to an unknown third party.
The objective checks flag it as executes-code, indicating the ability to run code or processes locally; this is a normal high-privilege capability for MCP tools and warrants caution, but by itself is not enough to classify it as high risk.
Its stated functions—file locking, commit approval, and agent coordination on the same codebase—reasonably imply access to the local repository and related file metadata; there is no evidence of system-level overreach beyond the stated purpose, but repository access still warrants least-privilege caution.
There is a public GitHub repository under the MIT License, making the source theoretically auditable, which is a meaningful risk-reducing factor; however, it comes from a third-party registry, lacks a README, has 0 stars, and has unknown maintenance status, so transparency and maturity are limited and the source and dependencies should be reviewed in an isolated environment first.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "ACDP" yet — see the docs or source repo.
Use ACDP to coordinate 3 AI agents working in parallel on the same codebase: Agent A handles authentication, Agent B handles the payment API, and Agent C writes unit tests. Prevent conflicts with file locking, require commit approval before merging, and summarize each agent's change status at the end.
A coordination report including file lock assignments, conflict prevention results, commit approval records, and a progress summary for each agent.
Set commit approval rules in ACDP so that any AI agent modifying core config files or database migration scripts must request approval first. Simulate one agent submitting changes and show the approval, release, or rejection flow.
A clear approval workflow example showing how commits affecting high-risk files are intercepted, reviewed, and ultimately handled.
Using ACDP, show which AI agents are currently active in the codebase, which files each one has locked, who is waiting for approval, and suggest the next task allocation based on those states.
A real-time collaboration dashboard-style result listing agent status, file usage, pending approval queues, and recommended next task assignments.
Coordinate multiple coding agents safely within the same repository.
Enable AI coding agents to communicate, share state, and coordinate work in real time.
Coordinate multiple AI agents on software projects with shared tasks and context.
Coordinate AI coding agents with identities, inboxes, thread search, and file leases.
Coordinate specialized AI agents for software development, review, testing, and task tracking.
Enable AI agents to communicate, route messages, and collaborate through MCP.