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AgentGo

by Nishkalkashyapversion 0.3.1i★ –iRuns on your computer
Registry nameio.github.Nishkalkashyap/agentgo

Install

Overview

Description from the maker (original English)

Run Codex and Claude Code on your computer from an MCP client, and track or continue their runs.

PopNx MCP’s three pillars

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

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: Developer tools

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).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

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": {
    "agentgo": {
      "command": "npx",
      "args": [
        "-y",
        "agentgo-mcp",
        "stdio"
      ]
    }
  }
}

Run this in your terminal

claude mcp add agentgo -- npx -y agentgo-mcp stdio

Open in Cursor

Or copy the settings yourself

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

{
  "mcpServers": {
    "agentgo": {
      "command": "npx",
      "args": [
        "-y",
        "agentgo-mcp",
        "stdio"
      ]
    }
  }
}

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": {
    "agentgo": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "agentgo-mcp",
        "stdio"
      ]
    }
  }
}

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.

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 with the GitHub account Nishkalkashyap, which owns the repo

  • … 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 Developer toolsi

  • More stars than 0% of the other 4906 servers in this category
  • Published to the registry more recently than 57% of the other 4906 servers in this category
  • Basic checks equal to or better than 100% of the other 4906 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 AgentGo 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?

The registry does not list a required key, though some servers ask you to sign in on first use.

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 (0.3.1) reached the registry 32 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 4 days ago
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MCP server for terminal commands, file operations, and process management

Runs on your computer★ 10,225MITUpdated 16 days ago
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Cloudflare MCP

by cloudflare

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Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
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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.

AgentGo

AgentGo lets an AI assistant run Codex and Claude Code on your computer. It's an MCP server: once your MCP client is connected to it, the assistant can look around the projects you've allowed, hand a coding task to Codex or Claude Code, check on it while it works, and read the result.

AgentGo runs on the computer where your code and your logged-in codex and claude CLIs live, and puts itself behind a Cloudflare tunnel, so the assistant can reach it from anywhere: a cloud agent, your phone, or another laptop.

Read this first. The agents run as you, with your files, your logins and your git credentials, and they approve their own actions. Anyone who has the AgentGo password can make them do anything they'd do for you. Only give the password to clients you'd trust at your keyboard, and only add projects you'd let an agent loose on.

Why I built it

I got sick of Codex's remote connection and remote device setup. I never got it working reliably, and when it did work it was too slow. AgentGo is my answer to that.

What you need

  • macOS or Linux, with Node.js 24.13 or newer. AgentGo uses Node's built-in SQLite, which still prints an "experimental" warning.
  • codex, claude, or both, installed and logged in. AgentGo uses your existing logins and never asks for API keys. It's tested with Codex 0.160.1 and Claude Code 2.1.291.
  • ripgrep (rg) on your PATH, for the file search tools. On macOS: brew install ripgrep.
  • cloudflared for the tunnel. If you don't have it, AgentGo can download it for you (see below).
  • An MCP client that supports the Streamable HTTP transport and lets you set an Authorization header.

Getting started

Install the CLI and check that everything it needs is there:

npm install -g agentgo-mcp

agentgo doctor

This installs two commands, agentgo and agentgo-mcp. They're the same thing; this README uses agentgo.

doctor shows whether codex, claude, rg and cloudflared are installed and whether you're logged in to each agent.

Next, tell AgentGo where your projects are. Point it at the folder they live in, and every folder inside it becomes a *workspace* that agents can work in:

agentgo workspace add-folder ~/code

Each workspace is named after its folder, so ~/code/my-app becomes my-app (spaces and other odd characters turn into dashes). Projects you create later show up on their own, and hidden folders are skipped. To add a single project that lives somewhere else, give it a name yourself:

agentgo workspace add notes ~/Documents/notes

agentgo workspace list shows what agents can see, and agentgo workspace remove takes something away. Changes apply straight away, even while the server is running.

Then start the server:

agentgo start

This starts AgentGo in the background along with a Cloudflare tunnel, then prints an MCP URL and the header to send with it:

MCP URL:       https://<random-words>.trycloudflare.com/mcp

Header name: Authorization Header value: Bearer

Add both to your MCP client. Include the word Bearer and the space after it.

The password is created the first time you run start and reused after that. Running start again while the server is up just prints it again. To replace it, run agentgo token rotate; the old one stops working straight away.

If cloudflared isn't installed, start stops and tells you. Install it yourself (brew install cloudflared on macOS), or run agentgo start --yes to let AgentGo download the official release from GitHub and check it against its published checksum. Pass --cloudflared if yours is somewhere unusual.

Managing the server
agentgo status

agentgo stop agentgo restart

You don't need to restart after changing workspaces, models or settings; the server picks up changes on the next request. Stopping the server interrupts any runs in progress. Edits they already made stay, but nothing is undone or resumed automatically.

If the server won't start, its log is at ~/.agentgo/daemon.log.

Add --json to any command if you're calling it from a script. The password is in the token field.

A stable address

By default you get a Cloudflare Quick Tunnel. It needs no Cloudflare account, but its URL changes every time the tunnel starts or reconnects. If you have a domain on Cloudflare, you can use a fixed address instead:

agentgo stop

agentgo start --custom-domain-with-cf agents.example.com

If cloudflared isn't logged in to your Cloudflare account yet, this opens a browser so you can log in. AgentGo then creates a tunnel in your account (or reuses the one it made before) and adds a DNS record for the hostname. It won't overwrite a DNS record that already exists.

If you'd rather manage the tunnel in the Cloudflare dashboard, point its public hostname at http://127.0.0.1:8765, save the tunnel token to a file, and run:

agentgo start --tunnel-token-file ~/tunnel-token --hostname agents.example.com --port 8765

start remembers how it was last started, so later start and restart calls reuse the same tunnel. Pass --quick to go back to a Quick Tunnel, or --local to listen on 127.0.0.1 with no tunnel at all.

If the tunnel drops, AgentGo reconnects it in the background. Runs in progress aren't affected.

Local only, over stdio

If your MCP client runs on the same computer, it can launch AgentGo directly instead:

{

"mcpServers": { "agentgo": { "command": "agentgo", "args": ["stdio"] } } }

There's no tunnel or password in this mode. Runs only last as long as the client keeps AgentGo open: when the client disconnects, runs in progress are interrupted.

The stdio server and the background server can't use the same state directory at the same time. Either stop the background server first, or give the stdio one its own directory with "args": ["stdio", "--state-dir", "/path"] and add workspaces to it with the same --state-dir.

What the assistant can do

AgentGo gives the assistant 13 tools.

Finding its way around. These read files directly. They don't start an agent.

ToolWhat it does
listWorkspacesLists the projects you've added
listDirectoryLists the files and folders in a directory
readFileReads lines from a text file
globFilesFinds files by name pattern, such as src/**/*.ts
grepFilesSearches file contents with ripgrep

Running agents.

ToolWhat it does
getAgentCapabilitiesShows which agents are installed and their versions
getSupportedModelsLists the models, effort levels and service tiers each agent accepts
startAgentRunGives Codex or Claude Code a task in a workspace
getAgentRunStatusChecks whether a run is queued, running or finished
getAgentRunOutputReads what the agent said and did, and its final answer
listAgentRunsLists past and current runs
cancelAgentRunStops a run
continueAgentSessionSends a follow-up to a finished run, in the same conversation

A run started by the assistant looks like this:

{

"provider": "codex", "model": "gpt-6.1-sol", "effort": "high", "serviceTier": "priority", "workspaceId": "my-app", "prompt": "Fix the failing tests and explain what was wrong.", "idempotencyKey": "fix-tests-1" }

It returns straight away with a taskId and a sessionId. The assistant then polls getAgentRunStatus and reads the result with getAgentRunOutput. To follow up, it calls continueAgentSession with the sessionId and a new prompt.

A few things worth knowing:

  • Agents approve their own actions. Codex runs with its workspace-write sandbox and its automatic reviewer (auto_review). Claude Code runs in auto mode with permission prompts turned off. Their reviewers can still refuse an action. Nobody is there to answer questions mid-run, so if Codex asks for input, the run fails with INPUT_REQUIRED. There's no option to bypass permissions entirely.
  • The browsing tools are limited; the agents aren't. readFile, grepFiles and the rest stay inside the workspace, don't follow symlinks, and refuse secrets such as .env, .ssh, .aws, .git, .npmrc and private keys. Agents are only held back by their own sandbox and reviewer, so they can read and run whatever those allow.
  • Search skips dependencies and build output. globFiles and grepFiles search one workspace at a time, up to 100,000 files. They follow .gitignore, skip hidden files, and skip folders such as node_modules, vendor, dist, build, target, .venv and __pycache__ wherever they appear. listDirectory and readFile can still open those.
  • Models aren't guessed. The assistant should call getSupportedModels first. Codex reports its own list. For Claude, AgentGo starts with the sonnet and opus aliases at low, medium and high effort; add others with agentgo model add claude-sonnet-5-5 --efforts low,medium,high,xhigh,max. An unknown model, effort or tier is an error, never silently swapped. Leave out serviceTier for Claude.
  • Up to five runs at once. They can be in different workspaces or the same one. Agents in the same workspace don't know about each other, so give parallel runs separate parts of the code. Extra runs wait in a queue.
  • Retries won't start a second run. Each run carries an idempotencyKey. If the assistant retries with the same key and arguments, it gets the original run back. Reusing a key with different arguments is an error.
  • Runs have a time limit. 30 minutes unless the assistant asks for longer with limits.wallTimeSeconds, up to an hour by default.
  • `succeeded` means the agent finished. It doesn't mean the tests pass or the change is right.
  • The assistant sees what the agent shows. Run output includes the agent's messages and the tools it used. For Codex it also includes the commands it ran, their output, and the files it changed. Hidden reasoning isn't included. If an agent prints a secret it read, that will be in the output too.

Where AgentGo keeps its state

Everything lives in ~/.agentgo: your workspaces and settings, the password, tunnel settings, run history, the server log, and cloudflared if AgentGo downloaded it. Use --state-dir or the AGENTGO_HOME environment variable to put it somewhere else. Workspaces can't be inside it, or contain it.

Run history is kept for 30 days. After that, prompts and output are deleted, but a small record of each run stays so a very late retry still can't start it again. Codex and Claude Code keep their own conversation history separately, and AgentGo doesn't touch it.

If the server stops unexpectedly, runs that were in progress are marked interrupted when it next starts. They're never re-run automatically; check the workspace for half-finished changes and continue the session yourself if you want.

Agents don't inherit your whole environment. They get PATH, HOME, locale, proxy settings, and the variables Codex and Claude Code use to log in (OPENAI_*, ANTHROPIC_*, and the AWS, Google and Azure ones). The AgentGo password is never passed to them.

agentgo config show prints the current settings. You can change these in ~/.agentgo/config.json:

SettingDefaultWhat it controls
maxConcurrentRuns5Runs that can go at once (up to 8)
maxQueuedRuns100Runs that can wait in the queue
maxRunSeconds3600The longest time limit a run can ask for
maxRunOutputBytes10 MiBOutput a run can produce before it's stopped
retentionDays30How long prompts and output are kept

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