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smallpeanutbaby/little-peanut-agent

Analysis updated 2026-06-24

13TypeScriptAudience · developerComplexity · 4/5Setup · moderate

TLDR

Electron desktop AI workbench with modes for chat, planning, agent execution, and review, plus a permission-gated local tool layer and SQLite store.

Mindmap

mindmap
  root((little-peanut-agent))
    Inputs
      User prompts
      Project folder
      MCP servers
      API keys
    Outputs
      Edited files
      Tool runs
      Saved memory
      Cost logs
    Use Cases
      Local coding agent
      Plan only research mode
      Pipeline planner executor reviewer
    Tech Stack
      Electron
      React
      TypeScript
      SQLite
      MCP
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Code map

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filefunction / class

What do people build with it?

USE CASE 1

Run a local AI workbench that edits files and runs commands inside a project

USE CASE 2

Use plan mode to research a change and propose a structured implementation

USE CASE 3

Chain planner, executor, and reviewer roles through pipeline mode

USE CASE 4

Connect MCP servers over stdio, SSE, or HTTP to add new agent tools

What is it built with?

ElectronReactTypeScriptSQLiteNodeMCP

How does it compare?

smallpeanutbaby/little-peanut-agentandersondanieln/hexllamabb8ad8/addroid-oss
Stars131313
LanguageTypeScriptTypeScriptTypeScript
Setup difficultymoderateeasyhard
Complexity4/52/54/5
Audiencedevelopervibe coderpm founder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Needs Node 22 or newer plus npm 10, and the real Electron app lives inside the src directory under a delegator root.

In plain English

Little Peanut is a desktop AI workbench built as an Electron application with a React interface and a local SQLite database. Its goal is not to be another chat client. The README frames it as a place where a model can actually do work inside a real project folder on your computer, rather than just answering questions in a browser tab. The repo is described as early development, with the basic skeleton in place and many features still being filled in. The app organises work into named modes. Chat is for light conversation, Agent runs tasks against a project, Plan is a read-only mode that does research and proposes a structured implementation plan without changing files, and Pipeline strings together a planner, executor, and reviewer in stages. There are also modes called Review, Writing, Code, Learning, Research, Brainstorm, Translate, and Summarize, each tuned for a different kind of request. The agent can call local tools such as file read and search, file edits, terminal commands, todo and task tracking, web search and fetch, lint reading, and a memory store. Tool calls go through a permission gate. Risky or destructive actions trigger an approval prompt, and permission rules can be saved per project or per session. The README is careful to say this is not a full sandbox, only a controllable boundary on a local machine. Little Peanut supports several model providers including OpenAI, Anthropic, Gemini, and OpenAI-compatible endpoints, with custom base URLs and API keys. It can also connect to MCP servers over stdio, SSE, or HTTP for extra tools. SQLite stores conversations, messages, tool runs, tasks, permission rules, a memory index, cost logs, model and provider config, and channel bot settings for QQ, Feishu, and DingTalk integrations. To run it you need Node.js 22 or newer and npm 10 or newer. The root folder is a small delegator, and the real Electron app lives in the src directory. Typical commands are npm install, npm run install:app, npm run dev to start, and npm run build or npm run dist to package.

Copy-paste prompts

Prompt 1
Install Node 22, run npm install and npm run install:app, then start the desktop app
Prompt 2
Walk through how permission gating decides which tool calls require an approval prompt
Prompt 3
Add an Anthropic provider with my API key and switch the active model in settings
Prompt 4
Wire a stdio MCP server into the agent and verify its tools show up in the picker
Prompt 5
Show me the SQLite tables that track tool runs, tasks, and permission rules

Frequently asked questions

What is little-peanut-agent?

Electron desktop AI workbench with modes for chat, planning, agent execution, and review, plus a permission-gated local tool layer and SQLite store.

What language is little-peanut-agent written in?

Mainly TypeScript. The stack also includes Electron, React, TypeScript.

How hard is little-peanut-agent to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is little-peanut-agent for?

Mainly developer.

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