mcpField
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CacheBash

CacheBash

Remote
github.com/rezzedaiAI & Agents0Updated 2d ago
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About CacheBash

CacheBash is an MCP server for coordinating AI coding agents and connecting them with a phone. It supports task dispatch, agent messaging, session monitoring, and human approvals through a mobile app and CLI.

Key features

  1. 01Task queues and dispatch
  2. 02Inter-agent messaging
  3. 03Session monitoring and alerts
  4. 04Mobile approval requests
  5. 05Sprint orchestration
  6. 06Overnight execution with budget caps

Use cases

  1. 01Assigning coding tasks from a phone
  2. 02Passing work between agent sessions
  3. 03Answering agent questions away from a terminal
  4. 04Coordinating dependent tasks across workstreams

MCP support

CacheBash exposes coordination tools through a Streamable HTTP MCP server with Bearer token authentication. It supports Claude Code, Cursor, VS Code + Copilot, Gemini CLI, and other MCP-compatible clients.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://cachebash-mcp-922749444863.us-central1.run.app/v1/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

All endpoints
Streamable HTTPhttps://cachebash-mcp-922749444863.us-central1.run.app/v1/mcpAuth required

Tools

Details

From the project README

CacheBash

CI

The coordination layer between your AI coding agents and your phone.

Your AI agents can't reach you when you close the laptop. CacheBash connects them. Task queues, relay messaging, session monitoring, human-in-the-loop approvals. One MCP server. Every client that speaks the protocol.


The Problem

You're running AI agents in your terminal. They write code, run tests, make decisions. But the moment they need your input, everything stops. You're at lunch. You closed the laptop. You're in a meeting.

Your agents can't coordinate with each other without you copying context between sessions. They can't ask you a question unless you're staring at the terminal. They can't run overnight because nobody's there to answer when they get stuck.

The Fix

npx cachebash init

One command. Authenticates via browser. Injects the MCP config into your Claude Code, Cursor, or VS Code setup. Done. Under 60 seconds.

Open the mobile app. Your agents appear. Send tasks, answer questions, monitor sessions — all from your phone.


What It Does

Task Queues — Dispatch work from your phone. Your agent picks it up in the terminal. Create tasks while you're away from your desk. Agents execute when they check in.

Relay Messaging — Your agents talk to each other through CacheBash. Agent A creates a task. Agent B claims it. Direct messaging, multicast to groups, delivery confirmation. No copy-paste. No you in the middle.

Session Monitoring — See which agents are running, what they're working on, how far along they are. Real-time updates. Push notifications when something needs your attention.

Human-in-the-Loop — Agent needs a decision? Your phone buzzes. Read the context. Tap to respond. The agent continues. You never opened a laptop.

Dream Mode — Dispatch work before bed. Set budget caps. Agents execute autonomously overnight. Wake up to pull requests, not a blank terminal.

Sprint Orchestration — Group related tasks into sprints with wave-based execution. Define dependencies between stories. Track progress across parallel workstreams.


Supported Clients

ClientStatus
Claude CodeSupported
CursorSupported
VS Code + CopilotSupported
Gemini CLISupported
Any MCP-compatible clientSupported

CacheBash uses Streamable HTTP transport with Bearer token auth. Standard MCP protocol. No vendor lock-in.


34 MCP Tools

Organized into 8 modules:

ModuleWhat It DoesTools
DispatchTask lifecycle — create, claim, complete, querycreate_task, get_tasks, claim_task, complete_task
RelayInter-agent messaging with delivery confirmationsend_message, get_messages, get_sent_messages, query_message_history
PulseSession health — create, update, list, heartbeatcreate_session, update_session, list_sessions
SprintParallel work orchestration with dependenciescreate_sprint, update_sprint_story, add_story_to_sprint, complete_sprint, get_sprint
SignalPush notifications and mobile questionsask_question, get_response, send_alert
DreamAutonomous overnight execution with budget capsdream_peek, dream_activate
StatePersistent per-program memory across sessionsget_program_state, update_program_state
KeysAPI key lifecycle — create, revoke, listcreate_key, revoke_key, list_keys
ObservabilityAudit logs, metrics, cost tracking, tracesget_audit, get_comms_metrics, get_cost_summary, get_operational_metrics, query_traces

Full reference: docs.rezzed.ai


Quick Start

Hosted (Recommended)
# 1. Install and authenticate
npx cachebash init

# 2. Verify connection
cachebash ping

# 3. Open the mobile app — your agent appears

The hosted version runs on Google Cloud. Free tier: 3 programs, 500 tasks/month, 1 concurrent session.

Self-Hosted
# 1. Clone the repo
git clone https://github.com/rezzedai/cachebash.git
cd cachebash

# 2. Install dependencies
cd services/mcp-server && npm install

# 3. Set up Firebase
# Create a Firebase project, enable Firestore
# Download service account key → set GOOGLE_APPLICATION_CREDENTIALS

# 4. Configure environment
cp .env.example .env
# Edit .env with your Firebase project details

# 5. Start the server
npm start

# 6. Configure your MCP client
# Add to your Claude Code / Cursor MCP config:
{
  "mcpServers": {
    "cachebash": {
      "url": "http://localhost:3000/v1/mcp",
      "headers": {
        "Authorization": "Bearer YOUR_API_KEY"
      }
    }
  }
}

Architecture

┌─────────────┐  ┌─────────────┐  ┌─────────────┐
│ Claude Code  │  │   Cursor    │  │   VS Code   │
└──────┬───────┘  └──────┬───────┘  └──────┬───────┘
       │                 │                 │
       └────────────┬────┴────────────────┘
                    │  MCP Protocol
                    ▼
          ┌─────────────────┐
          │  CacheBash MCP  │
          │     Server      │
          │  (Cloud Run)    │
          └────────┬────────┘
                   │
          ┌────────┴────────┐
          │                 │
          ▼                 ▼
   ┌────────────┐   ┌────────────┐
   │  Firestore  │   │ Mobile App │
   │  (Storage)  │   │  (iOS/And) │
   └─────────────┘   └────────────┘
  • MCP Server: TypeScript, runs on Cloud Run (or any Node.js host)
  • Storage: Google Cloud Firestore (multi-tenant, per-user isolation)
  • Auth: Firebase Auth (GitHub + Google OAuth) + per-program API keys
  • Mobile: React Native + Expo (iOS + Android)
  • Transport: Streamable HTTP with Bearer token auth

Project Structure

cachebash/
├── apps/
│   └── mobile/          # Mobile app (React Native + Expo)
├── services/
│   ├── mcp-server/      # MCP server (TypeScript, Cloud Run)
│   └── functions/       # Cloud Functions (auth, notifications, cleanup)
├── packages/
│   ├── cli/             # CLI tool (npx cachebash)
│   └── types/           # Shared TypeScript types
├── infra/               # Firebase rules and indexes
├── docs/                # Documentation
├── turbo.json           # Turborepo build orchestration
└── package.json         # npm workspaces root

Pricing

FreeProTeam
Price$0$29/mo$99/mo
Programs3UnlimitedUnlimited
Tasks/month500UnlimitedUnlimited
Concurrent sessions1510

You bring the models. CacheBash runs the orchestra. We never touch your LLM API keys.

Free tier is real. 500 tasks/month runs a serious workflow. Upgrade when you outgrow it.


Contributing

CacheBash MCP server is MIT licensed. Contributions welcome.

# Set up development environment
git clone https://github.com/rezzedai/cachebash.git
cd cachebash
npm install          # installs all workspaces
npm run dev

See CONTRIBUTING.md for guidelines.


Links


License

MIT — see LICENSE

Built by Rezzed.ai

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.