Run your AI coding agents as one coordinated team.

An open-source MCP server that connects Claude Code, Codex CLI, Gemini CLI, Goose, and more into a single autonomous mesh. Local-first. No cloud. No telemetry.

Open source on npmMIT licensemacOS · Linux
$ npx claudelink init --all --global
Loading the mesh…
ClaudeLink

The problem

One agent is fast. A team is a different category.

Five agents that own slices of the work, talk to each other, review, and retry beat any single session. The blocker was always the human typing “check messages” into every terminal. ClaudeLink removes that human.

Without ClaudeLink

With ClaudeLink

Without ClaudeLink: One agent per task

With ClaudeLink: A coordinated swarm: reviewer, developer, tester, ops

Without ClaudeLink: One model per task

With ClaudeLink: Mix Claude, Codex, Gemini, and Goose freely on the same mesh

Without ClaudeLink: You shuttle messages by hand

With ClaudeLink: Agents message each other directly

Without ClaudeLink: You poll every terminal for updates

With ClaudeLink: Auto-nudge wakes the right agent at the right time

Without ClaudeLink: No single view of the work

With ClaudeLink: Live Command Center at 127.0.0.1:7878

Without ClaudeLink: Every session is amnesiac to the others

With ClaudeLink: Shared SQLite mesh and a persistent bulletin board

How autonomy works

The loop that runs without you

No forged tool calls, no injected prompts, no unsafe shortcuts. A simulated keystroke routes through the agent's normal trusted-input pipeline, which is exactly why it works identically for Claude Code, Codex, Gemini, and Goose.

1

A message lands

Agent A calls send(). The message is a row in a local SQLite database, unread.

2

The scheduler notices

Every few minutes the auto-nudge scheduler queries for agents with unread mail. Only terminals that actually have mail get woken.

3

A keystroke, not an API call

ClaudeLink types "check for updates" into the right terminal, through tmux or iTerm2, exactly as you would.

4

The agent acts on its own

The receiving agent reads its inbox with its own tools, decides, and replies. The loop continues without you.

Command Center

A live console for the whole mesh

A local web UI at 127.0.0.1:7878. It boots with the first agent, survives restarts, and auto-refreshes every two seconds. Nothing about it leaves your machine.

Registered agents

Every agent with role, status, sent and received counts, last-seen, and a per-agent auto-reply toggle.

Auto-nudge control

Global on and off plus the tick interval. The scheduler only fires for terminals that actually have unread mail.

Health

Unread counts, bulletin entries, orphan blockers, and a one-click heal for dead-agent rows.

Recovery Watcher

Detects API rate-limit and overload errors in agent terminals and types a recovery prompt automatically.

Fleet live context

Per-agent context occupancy, cost per turn, and handoff freshness, sorted most-urgent-first.

Recent messages

A live feed of the last messages across all agents, with priority and unread badges.

Fleet live context · v1.5.0

See every context window. Compact with consent.

Long-running agents silently fill their context windows, and an uncontrolled auto-compact can wipe hours of in-flight work. ClaudeLink shows the whole fleet's occupancy live: percentage bars, cost per turn, handoff freshness, sorted most-urgent-first.

Fleet live context panel showing twelve agents with context occupancy bars, cost per turn, handoff freshness, and Compact and Clear buttons

A consent handshake, not a kill switch

Nothing fires blind. ClaudeLink first asks the agent to flush its handover and signal a checkpoint; only when the agent genuinely consents, and is re-confirmed idle, does the compact fire. Clear additionally refuses to run without a verified handoff. Nothing fires mid-work, and nothing fires without a yes.

Plan Usage · v1.6.0

Your subscription's real limits, as live meters

The five-hour session window, the weekly pool, and the frontier-model weekly pool, each with a reset countdown. Opt-in and local-only: a passthrough proxy reads the rate-limit headers your CLI already receives. Your token is never read and never logged.

Plan Usage tile showing session, weekly, and frontier-model usage meters with reset countdowns

Fleet Token Meter

The number that explains the whole idea

Consumption visibility for the entire fleet: lifetime tokens per agent, compaction history, and what that usage would have cost at API rates.

0M

tokens in one week

$0

API-equivalent value

0

agents on one mesh

One operator's fleet, one week: 606 million tokens, worth $1,330 at API rates, on a flat-fee subscription. The meter is how you know.

Fleet Token Meter showing 606 million total tokens, 1,330 dollars of API-equivalent value, and a per-agent lifetime usage table

Recovery Watcher · v1.4.0

Come back Monday to a fleet that never stopped

When the API rate-limits or overloads, a CLI halts mid-turn and waits for a human. The watcher spots the error in the terminal and types the recovery prompt for you, with cooldowns and an escalation threshold so it never spams a genuinely down API.

agent · developer

API Error: Server is temporarily limiting requests · Rate limited

[recovery-watcher] error detected · typing recovery prompt

check messages and continue with your current assignment

✓ agent resumed

Any model, any provider

The name says Claude. The mesh does not care.

Four CLIs are first-class with one-command install, and a single Goose terminal reaches 25+ providers. Pick the model for the job, per agent, with no ClaudeLink-side configuration.

Claude Code

Claude Opus, Sonnet, Haiku

Codex CLI

GPT-5 family

Gemini CLI

Gemini Pro and Flash

Goose

25+ providers

Anthropic ClaudeOpenAI GPTGoogle GeminixAI GrokMistralAWS BedrockGCP Vertex AIAzure OpenAIOpenRouterOllamaGroqDatabricks

One real recipe: a Claude reviewer for hard reasoning, a Codex developer, a Gemini tester, and a local Llama scaffolder via Ollama, all sharing the same SQLite mesh. The full provider list →

Patterns

What operators actually run

Code review pipeline

A developer agent writes, a reviewer agent critiques, and the loop runs until the diff is clean.

Test-driven loop

A tester agent writes failing tests; a developer agent makes them pass; neither waits for you.

Full team simulation

Architect, developers, reviewer, and ops roles on one mesh, coordinated by messages.

Parallel feature work

Several agents on the same codebase, each owning a slice, with a bulletin board for decisions.

Research swarm

Fan a question out to multiple agents on different models and let them compare notes.

Local-first

Built for people who read the source

Runs entirely on your machine; no cloud component exists

No telemetry, no analytics, no phone-home of any kind

No account, no sign-up, no API key of its own

All state is one SQLite file you can open and read

MIT licensed; every line is public and auditable

Agents keep full agency: ClaudeLink never forges a tool call

The details live on the features page and in the docs.

Get started

Three steps, then it runs itself

1Install and configure every CLI at once

$ npx claudelink init --all --global

2Restart your terminals

3Open the Command Center

$ claudelink ui
Junaid (Jay) Siddiqi, founder of RBJ Global LLC

Why I built this

I build software with a lot of AI coding agents running at once. ClaudeLink is the tool I made so they work as one coordinated team, and I open-sourced it so other builders can have it too.

Read the story

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