Ling Stack MCP Server

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Data Science & MLagentagent orchestrationagent skillsagentic aiai

Local-first AI teammate workspace. Bring your own models and keep project conversations, tool approvals, and results together.

Ling Stack is an open-source mcp server by ling-stack-org, written mainly in TypeScript, with 992 GitHub stars and the MIT license. Its code was last updated Nov 1, 2026.

<div align="center"> <img src="apps/web/public/icons/ling-mark.svg" alt="Ling Stack" width="88" height="88" /> <h1>Ling Stack</h1> <p><strong>Bring AI teammates into one local project workspace.</strong></p> <p>Choose their models. Keep conversations, tool approvals, and results together.</p> <p> English · <a href="README.zh-CN.md">简体中文</a> · <a href="README.ja-JP.md">日本語</a> · <a href="README.ko-KR.md">한국어</a> · <a href="README.de-DE.md">Deutsch</a> · <a href="README.fr-FR.md">Français</a> · <a href="README.es-ES.md">Español</a> · <a href="README.pt-BR.md">Português (Brasil)</a> </p> <p> <img alt="Source alpha" src="https://img.shields.io/badge/Status-source_alpha-5964a0.svg" /> <a href="LICENSE"><img alt="License: MIT" src="https://img.shields.io/badge/License-MIT-08765d.svg" /></a> <img alt="Node.js 22.22.1+" src="https://img.shields.io/badge/Node.js-22.22.1%2B-3c873a.svg" /> <img alt="pnpm 10" src="https://img.shields.io/badge/pnpm-10-f69220.svg" /> </p> <p> <a href="docs/community/first-project-review.md">Try a project review</a> · <a href="docs/getting-started.md">Getting started</a> · <a href="docs/troubleshooting.md">Troubleshooting</a> · <a href="docs/architecture.md">Architecture</a> · <a href="CONTRIBUTING.md">Contributing</a> · <a href="CHANGELOG.md">Changelog</a> </p> </div>

[!NOTE] Source-first alpha. Start with the Web UI, local daemon, and CLI from source. Desktop development is available separately; stable signed installers and a supported production release are not available yet.

Start With One Shared Task

When work involves several models, the task, their responses, tool requests, and results can end up in separate windows. Ling Stack brings that work into a project channel: give teammates model and tool bindings, review their activity, and keep the outcome with the conversation.

Try a bounded project document review with two teammates and a public sample brief. Begin with discussion; add tools and permissions when a later task needs them. Your own provider configuration and API key are required, and provider charges apply.

Ling Stack English homepage in a fresh workspace

English interface in a fresh local workspace with a non-secret demonstration model selected. No external model request was made. This capture shows the workspace layout, not a completed task. Follow the review guide above to try your own first collaboration.

Who Is It For?

Ling Stack is for developers and people who work with several AI models or teammates and want to keep their work in one place. It connects OpenAI, Anthropic, Volcengine Ark, DeepSeek-compatible endpoints, MiniMax, GLM, and OpenAI-compatible relays through a shared Model Workbench.

Workspace state, conversation history, and run evidence are stored locally. Requests and their context go to the model or tool providers you choose. The interface offers 55 language and region options; interface language and AI response language can be configured separately. README translations cover the eight languages linked above, not every interface locale. Other documentation may still be in English or Chinese.

Three Ways To Use It

ScenarioWhat you doWhat stays together
Ask a modelConfigure a chat model and start a conversation about a document, idea, or projectMessages, model selection, attachments, and results
Work with AI teammatesGive teammates model and tool bindings, then collaborate in a project channelParticipants, tool activity, approvals, artifacts, and the final report
Create mediaConfigure an image or video capability and use Media ProductionProjects, scenes, generation jobs, and outputs

Begin with a simple conversation, then add teammates or tools when the work needs them. Skills provide instructions; tool access and permission remain explicit. Coding-agent work uses the Pi runtime adapter, and available execution tools depend on platform setup and workspace policy.

Quick Start From Source

Requirements: Git, Node.js 22.22.1 or newer, Corepack with pnpm 10, and Rust with Cargo (install with rustup). The Web/daemon build compiles a native image sanitizer whose dependencies require Rust 1.89 or newer. CI uses Rust 1.97.1 and Node 22.22.1; the repository pins pnpm 10.0.0.

1. Install and build the local Web stack

git clone https://github.com/ling-stack-org/ling-stack.git
cd ling-stack
corepack enable
corepack pnpm install --frozen-lockfile
corepack pnpm --workspace-concurrency=1 --filter '@ling-stack/cli...' -r build

The filtered build includes the CLI, daemon, Web app, and their workspace dependencies. Desktop and Mobile builds have separate setup requirements.

On a fresh checkout, pnpm install may warn that the ling-stack-daemon bin cannot be linked because packages/daemon/dist/cli.js does not exist yet. Continue with the build above; use corepack pnpm ling for the source CLI. Node 22 may also print an experimental SQLite warning; that warning alone does not indicate a failed command.

2. Start the daemon

Keep this command running in the first terminal, from the repository root:

corepack pnpm ling daemon start --foreground

The default daemon address is http://127.0.0.1:17891. Keep it on loopback.

3. Open the Web UI

In a second terminal, from the same repository root:

corepack pnpm ling ui --foreground --open

Open http://127.0.0.1:5173 if the browser does not open automatically. In another terminal, curl http://127.0.0.1:17891/health should return JSON with "ok": true.

4. Connect a model and try a conversation

Open Settings → Model Workbench, add a chat-capable model with your own API key, and run Check. The first verified chat model becomes the workspace default. Start a new conversation and ask a small question, then inspect the response and its details.

After configuring and checking the model, run:

corepack pnpm ling doctor

Doctor reports model readiness as well as local service health. A fresh workspace with no chat model reports a provider failure even when the daemon and Web UI are running.

Follow Getting started for the first model, conversation, and project channel. See Troubleshooting for setup errors.

Support And Limits

Surface or integrationCurrent scope
Web, daemon, and CLISource alpha; the default getting-started path
Electron DesktopDevelopment shell; platform setup and clean-machine acceptance remain separate gates
Chrome extension and Browser HostLocal development integration; Chrome Web Store publication pending
MCP and Plugin ManagerExplicit tool assignment, activation, and approval boundaries
Office and Computer Use native featuresPlatform-dependent development; consult the maintained implementation and release gates
Image and video generationProvider- and capability-dependent; selected live adapters still have open gates
MobileExperimental work outside the current product acceptance scope

Platform execution, accessibility, signing, and installer acceptance remain open for selected native features. The Implementation Status index records what is implemented and what still needs acceptance. A source build or focused test result does not establish installer readiness.

For questions and reproducible bugs, read Support and use the GitHub Issue forms. Maintenance is best effort. Report vulnerabilities through Security.

Desktop development

Desktop has additional requirements: Xcode Command Line Tools with Swift and codesign on macOS, or the .NET 8 SDK on Windows for the Office driver. The current Desktop distribution targets are macOS arm64 and Windows x64. Electron also needs its platform binary; see Desktop troubleshooting.

corepack pnpm --filter @ling-stack/desktop dev

For platform tools, build commands, and manual checks, follow the Mac and Windows development-package guide. Read Desktop release and acceptance before packaging for distribution. Public source publication and signed binary releases are separate steps.

Data And Permissions

Default workspace state is under .ling-stack/, including ling-stack.sqlite, sessions/, artifacts/, and logs/. Provider keys entered in Model Workbench are saved in local workspace storage. Environment and supported keychain references are also available; see Configuration and data.

Keep keys, databases, session logs, and private outputs out of Git and public reports. Workspace permissions govern file access, shell commands, external mutations, and paid generation. Review approval requests before accepting them. For storage migration, use the CLI storage flows.

Explore Or Contribute

If this workflow is useful to you, star the repository to follow its progress. Tell us what you tried, where the first task got stuck, and whether the result helped through the Issue forms.

The Web app (apps/web), Desktop shell (apps/desktop), and CLI (packages/cli) share the daemon (packages/daemon). Core domain logic, contracts, provider adapters, and runner integrations live under packages/.

Ling Stack is available under the MIT License. Community participation follows the Code of Conduct.

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