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Micro-Multi

Local multi-agent desktop workspace compatible with deepseek-harness (dsh) plugins. 本地多 Agent 桌面工作台,兼容 deepseek-harness(dsh)插件体系。

LKDenchin/Micro-Multicommunitylistedunreviewed

Set up

Runs on your computer. Pick your agent and operating system.

Before you start

  • uv (`curl -LsSf https://astral.sh/uv/install.sh | sh`)
~/Library/Application Support/Claude/claude_desktop_config.json
{
  "mcpServers": {
    "micro-multi": {
      "command": "uvx",
      "args": [
        "masp-workspace"
      ]
    }
  }
}

same format Cursor, GitHub Copilot CLI, Junie, JetBrains AI Assistant, Augment (Auggie CLI), Factory Droid, Kiro, Devin CLI +12

Values in angle brackets are placeholders. Restart Claude Desktop after editing its config.Claude Desktop docs

README

synced Oct 21, 2026

Micro-Multi is a local desktop workspace built around multi-agent collaboration. You describe the job; the lead agent splits it into assignments. After you approve the plan, members work within their file ownership and task dependencies, and the lead combines their results. Plans, member progress, tool output and code diffs share one workspace.

For an order API change, one member implements pagination, another writes boundary tests, and a third documents the parameters. Independent assignments can run together. A test task that needs the implementation waits for its report. The scheduler coordinates concurrent writes to the same file.

DeepSeek Harness (dsh) plugin compatibility is the other core part of the project. Native Cordis Host and the dsh client module system load declared services, tools, settings forms and interface contributions. Enabled tools are available to team members as well as the lead. Skills and MCP services also work alongside these plugins.

Windows / Linux · English and Chinese · Your choice of model service · Apache-2.0

Why coordinate agents?

A single agent works well for short jobs. When implementation, tests and review share one execution loop, they usually happen in sequence and share one context. A prompt that says “divide the work” does not enforce who can edit which files, which task must wait, or whether an assignment has already started. That needs a scheduler.

A single agent, or agents without a coordinatorWhat Micro-Multi does
Implementation, tests and docs run in sequenceRuns independent tasks concurrently; dependencies wait for predecessor reports. Concurrency is bounded.
Several members edit the same fileUses declared file ownership, path locks and dependencies to coordinate writes.
Every role uses the same modelMembers inherit the lead model; you can change individual models in the plan.
Retries dispatch the same assignment againReuses running or completed assignments; an approved revision starts once.
Plugins are only wired to the leadEnabled dsh, MCP and command tools are available to the lead and members.

This compares execution models, not benchmark results. Parallel work can reduce waiting for independent tasks, but extra members can increase model calls and cost. Use the lead alone for a small edit; use a team when the responsibilities are clear.

Installation

Download a package from GitHub Releases.

SystemPackage
Windows x64NSIS installer
Debian / Ubuntu x64Debian package
Linux x64AppImage
ChecksumsSHA256SUMS.txt

On Windows, run the installer and open Micro-Multi from the Start menu. On Debian or Ubuntu, install the downloaded package with sudo apt install ./<package>.deb. For AppImage, make the file executable with chmod +x <file>.AppImage and run it. If FUSE is unavailable, add --appimage-extract-and-run.

The packages include Python and Node.js. Install Git for repository work. Docker and any CLI required by a plugin are installed separately. The desktop guide covers Linux keyring requirements, Ubuntu AppImage setup, checksums and building your own package.

Your first task

  1. Open Settings → Models → Add or edit model. Enter a name, API base URL, model ID and API key, then test the connection.

  2. Add a local project folder. Keep Link this directory selected to work in the original folder. A folder without Git is initialized as a repository.

  3. Start a conversation in that project. Select the model, Multi-agent collaboration, and the permissions you want to allow.

  4. Describe the change and how to check it. For example:

    Add pagination to the order API, keeping the existing response fields.
    Assign implementation, boundary tests and parameter docs to separate members.
    List their files and dependencies. The lead combines changes and runs tests.
    
  5. Review the plan in the chat. Adjust members, models or files, then confirm execution.

  6. Follow member progress and inspect the diff and test output. Send a follow-up in the same conversation if the result needs adjustment.

You can attach files to a conversation and open the right-hand inspector to browse files, reviews, previews and terminal activity. See projects and conversations for the main controls and model setup for connection details.

Working with a team

The lead prepares a plan with member roles, tasks, file ownership, dependencies and models. Use Adjust team to change it, then Confirm execution to start that revision. Member tasks do not run before approval. Each new task or round of feedback needs its own confirmation.

Confirmation checks the saved server revision. If a plan has changed, the chat card shows the updated assignments for review and confirmation in place. You do not need to open the collaboration map.

Members follow the lead model unless you select another model for them. The team view shows their status and reports; tool records show what they actually ran. You can add instructions while they work, pause the conversation or stop it. Before accepting the result, inspect the changes and the test output. The collaboration guide walks through this process.

Adding instructions and tools

Open Customization to manage extensions.

ExtensionUse it for
SkillsReusable instructions in a SKILL.md file. Project Skills live in .agents/skills/.
MCP serversTools provided by a configured local or remote server.
dsh pluginsNative Cordis services and tools, model providers, settings forms and conversation interface components.
Command pluginsTools implemented by a local command.

Open an installed plugin's details to configure it. A plugin may need its own account, API key or external program before its tools can be used. The composer + menu lists enabled capabilities. Read the extension guide to choose an extension type, or the dsh guide to install or develop a plugin.

Compatibility depends on a package's declared entries, dependencies and required services; it does not mean every third-party package has been tested. Startup restores the chat before loading optional plugin clients. Probing a plugin without a client does not boot its Host. Native services keep dsh's dependency and lifecycle rules.

Permissions and data

The composer offers three permission levels: Ask for approval asks before file changes and commands; Allow file edits allows file editing but still asks before commands; Full access permits file operations, commands and enabled external tools. The permissions guide explains what these settings control.

Projects, conversations and attachments are stored locally. Requests to your configured model service include the context needed for the task; enabled extensions may also send data to their services. Model-profile API keys use the operating system credential store. Local commands and native plugins run with your user account's system permissions.

Installed data lives in %APPDATA%\Micro-Multi\data on Windows and ${XDG_CONFIG_HOME:-~/.config}/Micro-Multi/data on Linux. Source mode uses .masp in the working directory. Set MASP_HOME to choose another directory. Updates and uninstall preserve the data; back it up separately from the application files.

Run from source

Use Python 3.11+, Node.js 24+, npm and Git. From the repository root:

python -m venv .venv

Activate the environment with .\.venv\Scripts\Activate.ps1 in Windows PowerShell, or source .venv/bin/activate on Linux. Then run:

python -m pip install -e ".[dev]"
npm ci
npm run desktop

To use a browser instead, run python -m masp.cli serve and open http://127.0.0.1:3080/. The deployment guide explains configuration and data storage.

Technology

LayerImplementation
DesktopElectron, with a sandboxed renderer and a preload bridge for desktop actions.
BackendPython, FastAPI, Uvicorn and Pydantic for local APIs and agent execution.
InterfaceHTML, CSS and JavaScript; React renders native plugin components.
Agent and plugin runtimeNode.js, Cordis and deepseek-harness packages.
StorageSQLite for application records, local files for attachments and the OS credential store for model keys.
ConnectionsHTTP APIs, SSE for streamed conversation events and WebSocket for plugin subscriptions.
Builds and documentationelectron-builder, esbuild and a static site generated from Markdown.

The architecture guide describes how these parts communicate and points to the relevant source directories.

Documentation and contributing

Start with model setup, projects and conversations, team collaboration and extensions. If something does not work as expected, see troubleshooting.

Report reproducible bugs in Issues, including the steps and sanitized logs. Questions and ideas belong in Discussions. Read CONTRIBUTING.md before submitting code. Report vulnerabilities through the private channel in SECURITY.md.

Micro-Multi is licensed under Apache-2.0. Third-party components retain their own licenses; see NOTICE and runtime provenance.

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