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codebase-context
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codebase-context

Active·★ 44·MIT·Updated 2026-05-11
★ Trending★ RAG / Knowledge Base★ Memory & Context

Second brain for AI agents working on your codebase - team coding patterns detection, persistent memory, preflight checks, and hybrid search with evidence scoring. Local-first MCP server.

Codebase-context is a local-first tool that acts as a second brain for AI agents, providing curated context on coding patterns, team conventions, and past decisions. It helps agents generate code that aligns with project standards, avoids repeated mistakes, and remembers crucial information across sessions.

#AI Agents#Codebase Context#Local-first#Developer Tools#Code Analysis#Team Memory#Coding Conventions#Retrieval-Augmented Generation (RAG)
$ Install
$ npx -y codebase-context /path/to/your/project
↗ Visit site★ GitHub
01

Features

01Curated context retrieval with pattern analysis and team memories.
02Automated detection of coding conventions, trends, and 'golden files'.
03Persistent memory for decisions, failures, and git commits with confidence decay.
04Preflight checks for code edits, including risk assessment and evidence validation.
02

Compatibility

Claude
AI Agent
Verified via docs
VS Code (Copilot)
IDE Integration
Verified via docs
Cursor
IDE Integration
Verified via docs
TypeScript
Language
Verified via docs
JavaScript
Language
Verified via docs
Python
Language
Verified via docs
03

Quick start

1
$ npx -y codebase-context /path/to/your/project
04

Use cases

↳Guiding AI agents to write code that adheres to specific team conventions and architecture.
↳Preventing AI agents from repeating past mistakes by surfacing failure memories and decisions.
↳Providing comprehensive context for AI agents before code modifications, including risk and best practices.
↳Automating the discovery of code patterns, golden files, and component usage for AI agents.
05

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Related searches

codebase-context AlternativesBest RAG / Knowledge Base Tools 2026Open Source RAG / Knowledge Basecodebase-context Tutorialcodebase-context Vs CompetitorsAI AgentsCodebase ContextLocal-first

Comments

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  • A
    Alex DavisMay 13, 2026

    Second brain for agents that detects team coding patterns is the right context architecture

  • H
    Harper GarciaMay 4, 2026

    The team pattern approach is more useful than generic code style guides

  • S
    Shawn ZhangApr 13, 2026

    Used for onboarding AI to legacy codebases, the pattern detection saves hours of context-setting

  • T
    Taylor NguyenApr 9, 2026

    Pattern detection from real team code gives AI suggestions that match actual conventions

On this page
01Features02Compatibility03Quick start04Use cases05Alternatives
Stats
GitHub Stars★ 44
Last commit2w ago
StatusActive
LicenseMIT
CategoryRAG / Knowledge Base
Trend (30d)
+1.7↑ 0.7%
Links
Documentation↗Discussion↗Issues↗Releases↗

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