Tares

Name: Tares
Author: glassflow

by glassflowversion 1.55.1i★ –iRuns on your computer

Registry nameai.glassflow/tares

Install

Overview

Description from the maker (original English)

Always-on AI agents: a software factory for Claude Code, or an AI SRE that watches your systems.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Other
You need to fill in: TARES_AUTH_TOKEN

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: TARESD_URL, TARES_AUTH_TOKEN

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "tares": {
      "command": "uvx",
      "args": [
        "tares",
        "mcp",
        "--transport",
        "stdio"
      ],
      "env": {
        "TARESD_URL": "your-value",
        "TARES_AUTH_TOKEN": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add tares --env TARESD_URL=your-value --env TARES_AUTH_TOKEN=your-value -- uvx tares mcp --transport stdio

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "tares": {
      "command": "uvx",
      "args": [
        "tares",
        "mcp",
        "--transport",
        "stdio"
      ],
      "env": {
        "TARESD_URL": "your-value",
        "TARES_AUTH_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "tares": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "tares",
        "mcp",
        "--transport",
        "stdio"
      ],
      "env": {
        "TARESD_URL": "your-value",
        "TARES_AUTH_TOKEN": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

TARESD_URL env
Address of the Tares the server talks to. Start one with `tares up`.
TARES_AUTH_TOKEN secret env
Token or API key for a Tares that has auth on. Leave empty for a local Tares without auth.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified against the domain glassflow.ai (the registry checks domain ownership)
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

More stars than 0% of the other 32680 servers in this category
Published to the registry more recently than 88% of the other 32680 servers in this category
Basic checks equal to or better than 100% of the other 32680 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Tares safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: TARES_AUTH_TOKEN

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.55.1) reached the registry 4 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, EmbeddedCI BenchPod

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Tares

The open-source platform for always-on AI agents.

Most agents wait for a prompt and forget everything when the session ends. Tares gives agents a place to work from: events from your systems land on one timeline per thing, agents wake when something happens, and what they decide (findings, plans, tickets, reviews, your answers) is kept for the next reader, human or agent. Works with Claude Code, Cursor, Codex and your own agents over MCP.

What you can build with it

Agents that watch your systems

Connect anything that emits events: logs, metrics, alerts, deploys, commits, database rows, webhooks. Tares merges them into one time-ordered timeline per service, repo, customer or job, and a trigger wakes an agent the moment something matters, with that timeline already in hand. The agent writes its conclusion back onto the timeline.

An AI SRE: an alert fires, the agent reads the service's whole history and writes the diagnosis before anyone opens a dashboard.
Shared code context: when a change matters, an agent updates the team's context repository with a pull request.
Anything with a failure mode: failed jobs, sandbox runs, voice calls, each with a timeline, a trigger and a finding that says what broke.

→ Build an AI SRE, Projects

A software factory

One crew of Claude Code sessions on your machine builds every project you hand it. You plan a project with Claude; an orchestrator hands out the tickets, builders open pull requests, a reviewer holds every change to a fixed bar, and builders merge once it passes and CI is green. You talk to one session, and only for decisions that are yours.

Plan once: a spec, milestones with acceptance checks, and tickets with a working doc each.
Build in parallel: one crew serves every project, a builder per milestone and repo.
Nothing is lost: tickets, reviews, the crew's assumptions and your answers live on Tares, so the crew carries on after a restart and you can check every choice it made.

→ Software factory, A project, end to end

Why Tares

One read instead of ten tool calls. An agent asks about a thing once and gets its correlated history across every source.
Agents that run on events, not prompts. Triggers wake your agent over MCP or a webhook, or run a Tares agent in-process.
A record that outlives the session. Findings, plans, tickets, reviews and decisions stay on Tares for the next reader.
Bring your own agent. Claude Code, Cursor, Codex or your own loop, over MCP. Any model provider for Tares's own agents.
Yours to run. MIT licensed, one daemon and one DuckDB file on your machine or server. No external database, no broker, no telemetry.

Quickstart

uv tool install tares                    # or: brew install glassflow/tap/tares

tares up # daemon + console on http://127.0.0.1:8787 tares mcp --transport streamable-http # in a second terminal: the MCP endpoint, :8788/mcp

Then pick what you came for.

Give an agent your systems. Add a source under Sources → Add source in the console (or start the demo stack to break something on purpose), and connect your agent:

claude mcp add --transport http tares http://localhost:8788/mcp

Ask it: *"Use tares: what happened to api-server in the last 15 minutes?"* → Quickstart

Build software with a crew. Needs Claude Code (signed in, on a plan with background sessions) and gh with write access to your repos:

tares factory crew up                         # start the crew; the first run asks how far it may go

tares factory spec "what you want to build" # in your repo: plan the project and hand it over tares factory crew attach orchestrator # answer the crew's questions

Watch it on the Crew page of the console. → Software factory

Prefer not to run it yourself? [Tares Cloud](https://console.tares-glassflow.com/) is the managed version, with the MCP endpoint already running.

Learn more


Concepts	sources, timelines, triggers, agents and projects
Connectors	Prometheus, OTLP, GitHub, Vercel, Postgres, webhooks, Claude Code sessions and more
Agents	connect any MCP client, or run Tares agents on a trigger
Software factory	the crew, its commands, and a project from spec to merged
Deployment	Docker, servers, TLS and auth
AI resources	for coding assistants: Markdown endpoints and instructions to paste

Feedback

Bug reports and ideas are welcome via GitHub issues or help@glassflow.ai.

License

MIT. This licence covers everything in this repository except directories named ee, which are under the licence in ee/LICENSE.

Tares

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Otheri

Common questions

Alternatives

Spec Driven Development

Remote Desktop Commander

EmbeddedCI BenchPod

README from the maker

Tares

What you can build with it

Agents that watch your systems

A software factory

Why Tares

Quickstart

Learn more

Feedback

License