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License: License: unverified
Local-run terms: Source code publicly available on GitHub; users can clone, read, modify, and run the tools locally with full workstation ownership.

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ai-whisper

FreeOpen SourceSelf-HostedAgentic

Pricing

Model
Free

Summary

Most AI coding agent setups quietly drift — context bleeds between sessions, agents stomp each other's work, and your preferences live in a config file you'll forget to back up. ai-creed is a family of six local-first tools built to give that control back to you.

The suite centers on ai-14all, a desktop app for running multiple coding agents in parallel across git worktrees — so agents work on separate branches without colliding. ai-cortex adds a local memory and context layer that persists between sessions without writing anything back to the repo. ai-whisper handles terminal-based relay between paired agents using structured workflows. The architecture is deliberately readable: the vendor states the codebase favors terseness and code you can audit end-to-end. Two tools — ai-samantha and ai-ezio — are still in active development, which means the ecosystem is incomplete for production voice or MCP hosting use cases today.

Bottom line: Pick ai-creed if you want parallel agents on isolated git branches with zero cloud dependency — but if you need a finished voice interface or a production-ready MCP host, two of the six tools are not there yet.

Community Performance Report Card

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Best For: Developers preferring local-first AI tooling, Users wanting readable, self-contained code for agent orchestration, Terminal and desktop workflows with git integration, Solo or small-team control over AI coding setups

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  • Parallel agents across git worktrees via ai-14all, so agents run on isolated branches and cannot overwrite each other's work — which means the collision problem that breaks single-worktree setups disappears by design.
  • Local memory and context layer via ai-cortex that persists across sessions without repo changes, so agents pick up where they left off without you re-seeding context every time.
  • Git-backed preference management via ai-pref-nsync, so your personal assistant configuration is versioned, portable, and not locked to a single machine or vendor account.
  • Fully open-source with a stated emphasis on readable, terse code, which means you can audit exactly what any agent is doing — no black-box runtime behavior to debug at 2am.
  • Self-hosted by default with no API dependency, so there is no service outage, pricing change, or deprecation that can break your workflow without your consent.
  • ai-samantha (voice companion) and ai-ezio (MCP host) are explicitly marked as works in progress and not production-ready — teams that need a voice interface or a generic MCP host today cannot rely on these two tools and will need to source alternatives or wait for the tools to stabilize.
  • There is no formal support channel beyond email and GitHub issues on an open-source project built by a small team — when something breaks in a sprint, the path to resolution is filing an issue or reading the source, not opening a support ticket.
  • The tooling is built for terminal and desktop workflows with tight git integration; teams whose agents need to operate inside a browser-based IDE, a CI pipeline, or a hosted environment will find the architecture does not extend to those surfaces without custom glue work — at which point teams with that requirement typically move to a platform that was built for hosted execution from the start.

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About

Platforms
Desktop, Terminal
API Available
No
Self-Hosted
Yes
Last Updated
2026-06-25T22:17:01.231Z

Best For

Who it's for

  • Developers preferring local-first AI tooling
  • Users wanting readable, self-contained code for agent orchestration
  • Terminal and desktop workflows with git integration
  • Solo or small-team control over AI coding setups

What it does well

  • Running multiple AI coding agents in parallel across git worktrees
  • Providing local context and memory for agents without repo changes
  • Relaying between paired AI coding agents via terminal workflows
  • Managing personal preferences for AI assistants via git
  • Building voice or workflow-native extensions for the ecosystem

Integrations

GitAI coding agents (ClaudeCodex)

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Frequently Asked Questions

Is ai-whisper free?
Yes — ai-whisper is fully free to use. There is no paid tier.
Is ai-whisper open source?
Yes. ai-whisper is open source.
Can I self-host ai-whisper?
Yes. ai-whisper supports self-hosting on your own infrastructure.
What platforms does ai-whisper support?
ai-whisper is available on: Desktop, Terminal.

Hours Saved & ROI Stories Community

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ai-whisper

ai-creed coordinates multiple AI coding agents running in parallel across git worktrees, keeping them from overwriting each other while maintaining per-session context and user preferences — all without touching a hosted service. The core workflow runs through ai-14all, which manages agent dispatch to separate worktrees via a desktop interface, while ai-cortex holds local memory and continuity data that agents can read across sessions. ai-whisper acts as a structured relay layer between paired agents in the terminal, and ai-pref-nsync stores personal assistant preferences in git so they travel with you and stay under version control.

The defining commitment across all six tools is local-first ownership. The vendor explicitly states the design favors terseness and code you can read end-to-end — no opaque runtime, no data leaving your workstation, no subscription gate on core functionality. For developers who have watched a SaaS-based agent tool change its pricing model or deprecate a workflow mid-project, that architecture is a functional guarantee, not a marketing position.

The suite fits solo developers and small teams who live in the terminal and want full visibility into what their agents are doing and why. It does not fit teams expecting a point-and-click setup with vendor support — this is open-source tooling built by a small group, and two tools (ai-samantha, the voice companion, and ai-ezio, the MCP host) are explicitly marked as works in progress. Bug reports and pull requests are the support channel. Teams that need a finished voice interface or a stable generic MCP host will find the ecosystem ahead of where those two tools currently stand.