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Mewbo logo

Mewbo

An open stack for agentic work, grounded in your own knowledge.

Ask DeepWiki Build and Push Docker Images Lint Docs Codecov GitHub Release Docker Image

Agentic task automation, memory-graph documentation and Q&A, and search across every tool you connect. Any model, open source.

Meeseeks.pre-alpha.demo.v2.mp4
MewboWiki overview page with a runtime flow diagram and inline Ask MewboWiki Q&A Stock ticker and GitHub repo card widgets rendered inline in the Mewbo Console
MewboWiki interactive knowledge graph of a repository Agentic Search: one ranked list of results across connected sources, topped by a synthesised overview
More screenshots: console, wiki, search, and integrations
A SESSION, END TO END
Mewbo console landing page listing recent sessions
Your sessions at a glance
Mewbo task detail page
Inside a task, step by step
Plan approval in the Mewbo console
Plan mode: approve before anything runs
File-edit diff card in the Mewbo console
Every edit lands as a reviewable diff
THE KNOWLEDGE PRODUCTS
Agentic Wiki landing page that generates source-grounded documentation from a repository URL
Agentic Wiki: documentation from a repo URL
Agentic Search landing page with workspaces scoped to connected sources
Agentic Search: workspaces over your connected tools
EXTEND IT, ON EVERY SURFACE
Plugins page with installed plugins and marketplace listings
Plugins and a marketplace to extend any session
Home Assistant device control via Mewbo
The same agent, controlling Home Assistant
Mewbo email thread in Gmail
Or working from your inbox over email

Overview

Mewbo is an open, model-agnostic stack for agentic work. At its core, a hypervisor decomposes a goal into parallel sub-agents that each carry only the tools they need and exchange compressed summaries instead of raw transcripts, within resource budgets you tune per deployment. Three products build on that core. The first automates multi-step tasks across your codebase and tools, isolating each change in its own Git worktree. The second generates living documentation and question answering, grounded in a multiplexed memory graph that runs alongside an AST index of your code. The third is a search engine rebuilt around agents and indexes, ranking results across every source you have connected. You approve destructive actions, watch the agent tree as it grows, and can steer any branch mid-flight. Sessions persist with full provenance, compact automatically near the budget, and run on any model across every client.

Features

  • Agent hypervisor. Sub-agents spawn in parallel with scoped tools and approval-gated actions. Progress shows as a live tree, and you can steer or cancel any branch mid-flight. The hypervisor enforces resource budgets through natural-language warnings rather than force-kills, and resolves every child into a structured result.
  • Long-horizon context. Two-mode compaction summarises older turns near the budget. Post-compact file restoration replays the working set. Conversation fork lets you branch from any message and replay against a different model.
  • Native skills, plugins, and MCP. Agent Skills, plugins from any compatible marketplace, and MCP servers load from user or project scope without translation. Plugins also contribute per-session stateful tools, hooks, and agent definitions.
  • Agentic Wiki. Turns any repository into living documentation you can interrogate. Indexing pairs a multiplexed memory graph with an AST index of the code, so question answering traverses structure and meaning across many hops for authoritative answers grounded in the source itself.
  • Agentic Search. A search engine rebuilt around agents and indexes. One query fans out across every source you've connected, from repos to trackers to chat, and comes back as one ranked list of results spanning them all, topped by a synthesised overview cited to its sources.
  • Inline interactive widgets. Sub-agents author Streamlit-in-WASM widgets that mount in a sandboxed Web Worker inside the conversation, with no server round-trip and no CORS.
  • Provider-agnostic, multi-surface. Any model behind LiteLLM, accessed from a terminal CLI, web console, REST API, Home Assistant, Nextcloud Talk, or email. Same session, same tools, same transcript.

Get started

See docs.mewbo.com/latest/getting-started to install Mewbo and run a first session.

Documentation

Full documentation lives at docs.mewbo.com.

Section Covers
Get Started Install, configure an LLM, run a first session.
Configure LLM setup, project config, configuration reference.
Clients CLI, web console, REST API, Home Assistant, Nextcloud Talk, email.
Knowledge & Discovery Agentic Wiki and Agentic Search, the source-grounded docs and cross-tool search products.
Capabilities Built-in tools, sub-agents, skills, plugins, widgets, plan mode, permissions, compaction.
Deploy Docker Compose, storage backends, production setup.
Develop Architecture, session runtime, building a client, API reference.
Releases Release notes and upgrade history.

Contributing

Bugs and feature requests on the issue tracker. For development setup, see the developer guide.

License

MIT © Krishnakanth Alagiri.

About

AI assistant with a built-in agent hypervisor. Spawns, scopes, and manages parallel sub-agents across tasks. Runs from your terminal, browser, API, or Home Assistant.

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