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‎README.md‎

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[![npm version](https://img.shields.io/npm/v/codebase-context)](https://www.npmjs.com/package/codebase-context) [![license](https://img.shields.io/npm/l/codebase-context)](./LICENSE) [![node](https://img.shields.io/node/v/codebase-context)](./package.json)
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You're tired of AI agents writing generic code that compiles but completely ignores how your team does things — even with well-curated instructions. You correct the agent, it doesn't remember. Next session, same mistakes.
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You're tired of AI agents writing code that 'just works' but fits like a square peg in a round hole - not your conventions, not your architecture, not your repo. Even with well-curated instructions. You correct the agent, it doesn't remember. Next session, same mistakes.
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This MCP gives agents *just enough* context so they match *how* your team codes, know *why*, and *remember* every correction.
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This MCP gives agents _just enough_ context so they match _how_ your team codes, know _why_, and _remember_ every correction.
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**Finds the right context** — Search that doesn't just return code. Each result comes back with pattern signals, related team memories, file relationships, and quality indicators. The agent gets curated context, not raw hits.
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Here's what codebase-context does:
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**Knows your conventions** — Detected from your code, not from rules you wrote. Adoption percentages, trend direction (rising/declining), golden files. What patterns the team is moving toward and what's being left behind.
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**Finds the right context** - Search that doesn't just return code. Each result comes back with analyzed -and quantified- coding patterns and conventions, related team memories, file relationships, and quality indicators. The agent gets curated context, not raw hits.
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**Remembers across sessions** — Decisions, failures, gotchas — recorded once, surfaced automatically. Conventional git commits (`refactor:`, `migrate:`, `fix:`) auto-extract into memory with zero effort. Stale memories decay and get flagged instead of blindly trusted.
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**Knows your conventions** - Detected from your code, not only from rules you wrote. Seeks team consensus and direction by adoption percentages and trends (rising/declining), golden files. What patterns the team is moving toward and what's being left behind.
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**Checks before editing** — A preflight card with risk level, patterns to use and avoid, failure warnings, and a `readyToEdit` evidence check. If evidence is thin or contradictory, it says so.
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**Remembers across sessions** - Decisions, failures, things that _should_ work but didn't when you tried - recorded once, surfaced automatically. Conventional git commits (`refactor:`, `migrate:`, `fix:`) auto-extract into memory with zero effort. Stale memories decay and get flagged instead of blindly trusted.
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One tool call returns all of it. Local-first — your code never leaves your machine.
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**Checks before editing** - A preflight card with risk level, patterns to use and avoid, failure warnings, and a `readyToEdit` evidence check. If evidence is thin or contradictory, it says so.
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One tool call returns all of it. Local-first - your code never leaves your machine.
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<!-- TODO: Add demo GIF here showing search_codebase with preflight card output -->
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<!-- ![Demo](./docs/assets/demo.gif) -->
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## Quick Start
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### Claude Code
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Add it to the configuration of your AI Agent of preference:
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No config file needed:
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### Claude Code
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```bash
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claude mcp add codebase-context -- npx -y codebase-context /path/to/your/project
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"servers": {
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"codebase-context": {
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"command": "npx",
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"args": ["-y", "codebase-context", "${workspaceFolder}"]
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"args": ["-y", "codebase-context", "/path/to/your/project"] // Or "${workspaceFolder}"if your workspace is one project only
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}
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}
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}
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}
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```
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## Codex
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Run codex mcp add codebase-context npx -y codebase-context "/path/to/your/project"
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## What It Actually Does
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Other tools help AI find code. This one helps AI make the right decisions — by knowing what your team does, tracking where patterns are heading, and warning before mistakes happen.
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Other tools help AI find code. This one helps AI make the right decisions - by knowing what your team does, tracking where codebases are heading, and warning before mistakes happen.
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### The Difference
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| Without codebase-context | With codebase-context |
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| --- | --- |
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| Generates code using whatever matches or "feels" right | Sees what's rising vs declining in your codebase |
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| Copies any example that fits | Follows your best implementations (golden files) |
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| Repeats mistakes you already corrected | Surfaces failure memories right before trying again |
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| You re-explain the same things every session | Remembers conventions and decisions automatically |
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| Edits confidently even when context is weak | Gets `readyToEdit: false` - knows to ask first |
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| Without codebase-context | With codebase-context |
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| ------------------------------------------------------- | --------------------------------------------------- |
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| Generates code using whatever matches or "sounds" right | Generates code following your team conventions |
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| Copies any example that fits | Follows your best implementations (golden files) |
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| Repeats mistakes you already corrected | Surfaces failure memories right before trying again |
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| You re-explain the same things every session | Remembers conventions and decisions automatically |
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| Edits confidently even when context is weak | Flags high-risk changes when evidence is thin |
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| Sees what the current code does and assumes | Sees how your code has evolved and why |
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### The Search Tool (`search_codebase`)
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```
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Risk level, what to use, what to avoid, what broke last time, and whether the evidence is strong enough to proceed — all in one response.
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Risk level, what to use, what to avoid, what broke last time, and whether the evidence is strong enough to proceed - all in one response.
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### Patterns & Conventions (`get_team_patterns`)
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Detects what your team actually does by analyzing the codebase:
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- Adoption percentages for dependency injection, state management, testing, libraries
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- Patterns/conventions trend direction (Rising / Stable / Declining) based on git recency
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- Golden files — your best implementations ranked by modern pattern density
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- Conflicts — when the team hasn't converged (both approaches above 20% adoption)
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- Golden files - your best implementations ranked by modern pattern density
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- Conflicts - when the team hasn't converged (both approaches above 20% adoption)
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### Team Memory (`remember` + `get_memory`)
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Record a decision once. It surfaces automatically in search results and preflight cards from then on. **Your git commits also become memories** — conventional commits like `refactor:`, `migrate:`, `fix:`, `revert:` from the last 90 days are auto-extracted during indexing.
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Record a decision once. It surfaces automatically in search results and preflight cards from then on. **Your git commits also become memories** - conventional commits like `refactor:`, `migrate:`, `fix:`, `revert:` from the last 90 days are auto-extracted during indexing.
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- **Types**: conventions (style rules), decisions (architecture choices), gotchas (things that break), failures (we tried X, it broke because Y)
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- **Confidence decay**: decisions age over 180 days, gotchas and failures over 90 days. Stale memories get flagged instead of blindly trusted.
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- **Zero-config git extraction**: runs automatically during `refresh_index`. No setup, no manual work.
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### All Tools
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| Tool | What it does |
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| --- | --- |
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| `search_codebase` | Hybrid search with enrichment. Pass `intent: "edit"` for preflight. |
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| `get_team_patterns` | Pattern frequencies, golden files, conflict detection |
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| `get_component_usage` | "Find Usages" — where a library or component is imported |
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| `remember` | Record a convention, decision, gotcha, or failure |
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| `get_memory` | Query team memory with confidence decay scoring |
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| `get_codebase_metadata` | Project structure, frameworks, dependencies |
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| `get_style_guide` | Style guide rules for the current project |
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| `detect_circular_dependencies` | Import cycles between files |
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| `refresh_index` | Re-index (full or incremental) + extract git memories |
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| `get_indexing_status` | Progress and stats for the current index |
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| Tool | What it does |
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| ------------------------------ | ------------------------------------------------------------------- |
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| `search_codebase` | Hybrid search with enrichment. Pass `intent: "edit"` for preflight. |
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| `get_team_patterns` | Pattern frequencies, golden files, conflict detection |
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| `get_component_usage` | "Find Usages" - where a library or component is imported |
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| `remember` | Record a convention, decision, gotcha, or failure |
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| `get_memory` | Query team memory with confidence decay scoring |
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| `get_codebase_metadata` | Project structure, frameworks, dependencies |
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| `get_style_guide` | Style guide rules for the current project |
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| `detect_circular_dependencies` | Import cycles between files |
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| `refresh_index` | Re-index (full or incremental) + extract git memories |
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| `get_indexing_status` | Progress and stats for the current index |
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## How the Search Works
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## Language Support
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Over **30+ languages** are supported: TypeScript, JavaScript, Python, Java, Kotlin, C/C++, C#, Go, Rust, PHP, Ruby, Swift, Scala, Shell, and common config/markup formats.
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However right now only **Angular** has a specific analyzer for enriched context (signals, standalone components, control flow, DI patterns).
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However right now only **Angular** has a specific analyzer for enriched context (signals, standalone components, control flow, DI patterns).
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If you need enriched context from any language or framework, please file an issue - or even better, contribute with a new analyzer
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Structured filters available: `framework`, `language`, `componentType`, `layer` (presentation, business, data, state, core, shared).
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## Configuration
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| Variable | Default | Description |
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| --- | --- | --- |
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| `EMBEDDING_PROVIDER` | `transformers` | `openai` (fast, cloud) or `transformers` (local, private) |
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| `OPENAI_API_KEY` | — | Required only if using `openai` provider |
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| `CODEBASE_ROOT` | — | Project root (CLI arg takes precedence) |
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| `CODEBASE_CONTEXT_DEBUG` | — | Set to `1` for verbose logging |
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| Variable | Default | Description |
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| ------------------------ | -------------- | --------------------------------------------------------- |
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| `EMBEDDING_PROVIDER` | `transformers` | `openai` (fast, cloud) or `transformers` (local, private) |
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| `OPENAI_API_KEY` | - | Required only if using `openai` provider |
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| `CODEBASE_ROOT` | - | Project root (CLI arg takes precedence) |
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| `CODEBASE_CONTEXT_DEBUG` | - | Set to `1` for verbose logging |
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## Performance
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```
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.codebase-context/
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memory.json # Team knowledge (commit this)
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memory.json # Team knowledge (should be persisted in git)
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intelligence.json # Pattern analysis (generated)
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index.json # Keyword index (generated)
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index/ # Vector database (generated)
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```
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## Tip: Auto-invoke in Your Rules
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## Tip: Ensuring your AI Agent recalls memory:
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Add this to `.cursorrules`, `CLAUDE.md`, or `AGENTS.md`:
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## Links
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- [Motivation](./MOTIVATION.md) — Research and design rationale
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- [Changelog](./CHANGELOG.md) — Version history
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- [Contributing](./CONTRIBUTING.md) — How to add analyzers
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- [Motivation](./MOTIVATION.md) - Research and design rationale
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- [Changelog](./CHANGELOG.md) - Version history
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- [Contributing](./CONTRIBUTING.md) - How to add analyzers
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## License
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