ragtime-cli 0.3.2

Local-first memory and RAG system for Claude Code - semantic search over code, docs, and team knowledge

ragtime-cli

Local-first memory and RAG system for Claude Code. Semantic search over code, docs, and team knowledge.

Two interfaces, same data:

• CLI for humans - formatted output, interactive workflows
• MCP for agents - structured data, tool integration

Features

• Memory Storage: Store structured knowledge with namespaces, types, and metadata
• Semantic Search: Query memories, docs, and code with natural language
• Code Indexing: Index functions, classes, and composables from Python, TypeScript, Vue, and Dart
• Cross-Branch Sync: Share context with teammates before PRs merge
• Convention Checking: Verify code follows team standards before PRs
• Doc Generation: Generate documentation from code (stubs or AI-powered)
• Debug Tools: Verify index integrity, inspect similarity scores
• MCP Server: Native Claude Code integration
• Usage Documentation: Guidance for integrating ragtime into AI workflows
• ghp-cli Integration: Auto-context when starting issues via hooks

Installation

pip install ragtime-cli

Quick Start

# Initialize in your project (prompts to set up MCP server)
ragtime init

# Or skip prompts with -y
ragtime -y init

# Or just enable MCP globally (works in any project)
ragtime init -G

# Index your docs
ragtime index

# Store a memory
ragtime remember "Auth uses JWT with 15-min expiry" \
  --namespace app \
  --type architecture \
  --component auth

# Search memories
ragtime search "authentication" --namespace app

# View usage documentation for AI integration
ragtime usage

# Check for updates
ragtime update --check

CLI Commands

Memory Storage

# Store a memory
ragtime remember "content" --namespace app --type architecture --component auth

# List memories
ragtime memories --namespace app --type decision

# Graduate branch memory to app
ragtime graduate <memory-id>

# Delete a memory
ragtime forget <memory-id>

Search & Indexing

# Index everything (docs + code)
ragtime index

# Incremental index (only changed files - fast!)
ragtime index  # ~8 seconds vs ~5 minutes for unchanged codebases

# Index only docs
ragtime index --type docs

# Index only code (functions, classes, composables)
ragtime index --type code

# Full re-index (removes old entries, recomputes all embeddings)
ragtime index --clear

# Semantic search across all content
ragtime search "how does auth work" --limit 10

# Search only code
ragtime search "useAsyncState" --type code

# Search only docs
ragtime search "authentication" --type docs --namespace app

# Hybrid search: semantic + keyword filtering
# Use -r/--require to ensure terms appear in results
ragtime search "error handling" -r mobile -r dart

# Reindex memory files
ragtime reindex

# Audit docs for missing frontmatter
ragtime audit docs/
ragtime audit docs/ --fix    # Interactively add frontmatter
ragtime audit docs/ --json   # Machine-readable output

Documentation Generation

# Generate doc stubs from code
ragtime generate src/ --stubs

# Specify output location
ragtime generate src/ --stubs -o docs/api

# Python only
ragtime generate src/ --stubs -l python

# Include private methods
ragtime generate src/ --stubs --include-private

Debug & Verification

# Debug a search query (show similarity scores)
ragtime debug search "authentication"
ragtime debug search "auth" --show-vectors

# Find similar documents
ragtime debug similar docs/auth/jwt.md

# Index statistics by namespace/type
ragtime debug stats
ragtime debug stats --by-namespace
ragtime debug stats --by-type

# Verify index integrity
ragtime debug verify

Cross-Branch Sync

# Sync all teammate branch memories
ragtime sync

# Auto-prune stale synced folders
ragtime sync --auto-prune

# Manual prune
ragtime prune --dry-run
ragtime prune

Daemon (Auto-Sync)

# Start background sync daemon
ragtime daemon start --interval 5m

# Check status
ragtime daemon status

# Stop daemon
ragtime daemon stop

Usage Documentation

# View all usage documentation
ragtime usage

# View specific sections
ragtime usage --section mcp        # MCP server integration
ragtime usage --section cli        # CLI workflow examples
ragtime usage --section workflows  # Common AI workflow patterns
ragtime usage --section conventions # Convention checking

# Set up ghp-cli hooks
ragtime setup-ghp

Storage Structure

.ragtime/
├── config.yaml              # Configuration
├── CONVENTIONS.md           # Team rules (checked by /create-pr)
├── app/{component}/         # Graduated app knowledge (tracked)
│   └── {id}-{slug}.md
├── team/                    # Team conventions (tracked)
│   └── {id}-{slug}.md
├── branches/
│   ├── {branch-slug}/       # Your branch (tracked in git)
│   │   ├── context.md
│   │   └── {id}-{slug}.md
│   └── .{branch-slug}/      # Synced from teammates (gitignored, dot-prefix)
├── archive/branches/        # Archived completed branches (tracked)
└── index/                   # ChromaDB vector store (gitignored)

Configuration

.ragtime/config.yaml:

docs:
  paths: ["docs"]
  patterns: ["**/*.md"]
  exclude: ["**/node_modules/**", "**/.ragtime/**"]

code:
  paths: ["."]
  languages: ["python", "typescript", "javascript", "vue", "dart"]
  exclude: ["**/node_modules/**", "**/build/**", "**/dist/**"]

conventions:
  files: [".ragtime/CONVENTIONS.md"]
  also_search_memories: true
  storage: auto  # auto | file | memory | ask
  default_file: ".ragtime/CONVENTIONS.md"
  folder: ".ragtime/conventions/"
  scan_docs_for_sections: ["docs/"]

How Search Works

Search returns summaries with locations, not full code:

1. What you get: Function signatures, docstrings, class definitions
2. What you don't get: Full implementations
3. What to do: Use the file path + line number to read the full code

This is intentional - embeddings work better on focused summaries than large code blocks. The search tells you what exists and where, then you read the file for details.

For Claude/MCP usage: The search tool description instructs Claude to read returned file paths for full implementations before making code changes.

Smart Query Understanding

Search automatically detects qualifiers in natural language:

# These are equivalent - qualifiers are auto-detected
ragtime search "error handling in mobile app"
ragtime search "error handling" -r mobile

# Use --raw for literal/exact search
ragtime search "mobile error handling" --raw

Auto-detected qualifiers include: mobile, web, desktop, ios, android, flutter, react, vue, dart, python, typescript, auth, api, database, frontend, backend, and more.

Tiered Search

Use tiered search to prioritize curated knowledge over raw code:

# Via MCP
search(query="authentication", tiered=True)

Tiered search returns results in priority order:

1. Memories - Curated, high-signal knowledge
2. Documentation - Indexed markdown files
3. Code - Function signatures and symbols

Hybrid Search

For explicit keyword filtering, use require_terms:

# CLI
ragtime search "error handling" -r mobile -r dart

# MCP
search(query="error handling", require_terms=["mobile", "dart"])

This combines semantic similarity (finds conceptually related content) with keyword filtering (ensures qualifiers aren't ignored).

Hierarchical Doc Chunking

Long markdown files are automatically chunked by headers for better search accuracy:

• Each section becomes a separate searchable chunk
• Parent headers are preserved as context in the embedding
• Short docs (<500 chars) remain as single chunks
• Section path is stored (e.g., "Installation > Configuration > Environment Variables")

Feedback Loop

Search quality improves over time based on usage patterns:

# Record when a result is useful (via MCP)
record_feedback(query="auth flow", result_file="src/auth.py", action="used")

# View usage statistics
feedback_stats()

Frequently-used files receive a boost in future search rankings.

Code Indexing

The code indexer extracts meaningful symbols from your codebase:

Language	What Gets Indexed
Python	Classes, methods, functions (with docstrings)
TypeScript/JS	Functions, classes, interfaces, types (exported and non-exported)
Vue	Components, composable usage (useXxx calls)
Dart	Classes, functions, mixins, extensions

Each symbol is indexed with:

• content: The code snippet with signature and docstring
• file: Full path to the source file
• line: Line number for quick navigation
• symbol_name: Searchable name (e.g., useAsyncState, JWTManager.validate)
• symbol_type: function, class, method, interface, composable, etc.

Example search results:

ragtime search "useAsyncState" --type code

[1] /apps/web/components/agency/payers.vue
    Type: code | Symbol: payers:useAsyncState
    Score: 0.892
    Uses composable: useAsyncState...

Memory Format

Memories are markdown files with YAML frontmatter:

---
id: abc123
namespace: app
type: architecture
component: auth
confidence: high
status: active
added: '2025-01-31'
author: bretwardjames
---

Auth uses JWT tokens with 15-minute expiry for security.
Sessions are stored in Redis, not cookies.

Namespaces

Namespace	Purpose
app	How the codebase works (architecture, decisions)
team	Team conventions and standards
user-{name}	Individual preferences
branch-{name}	Work-in-progress context

Memory Types

Type	Description
architecture	System design, patterns
feature	How features work
decision	Why we chose X over Y
convention	Team standards
pattern	Reusable approaches
integration	External service connections
context	Session handoff

AI Integration

Ragtime is designed to work seamlessly with AI agents via MCP tools. Run ragtime usage for comprehensive documentation on integration patterns.

Key Patterns

Memory Storage: Use remember to capture architectural decisions, patterns, and context:

remember("Auth uses JWT with 15-min expiry", namespace="app", type="architecture", component="auth")

Semantic Search: Use search for finding relevant code and documentation:

search("how does authentication work", tiered=True)  # Prioritizes curated knowledge
search("error handling", require_terms=["mobile", "dart"])  # Hybrid filtering

Convention Checking: Before PRs, verify code follows team standards:

ragtime check-conventions          # Filtered to changed files
ragtime check-conventions --all    # All conventions (for AI analysis)

Handoff Context: Save session state for continuity:

store_doc(content="Session summary...", namespace="branch-feature-123", doc_type="handoff")

Building Custom Commands

Create project-specific slash commands in .claude/commands/ that orchestrate ragtime tools:

# .claude/commands/my-workflow.md
1. Search for relevant context: search("$ARGUMENTS", tiered=True)
2. Store any new insights: remember(...)
3. Check conventions before suggesting changes

The real value is in the MCP tools - combine them however fits your workflow.

MCP Server

The MCP server is automatically configured during ragtime init. You can also set it up manually:

# Project-level: creates .mcp.json in current project
ragtime init

# Global: adds to ~/.claude/settings.json (works in any project)
ragtime init -G

Or add manually to .mcp.json:

{
  "mcpServers": {
    "ragtime": {
      "command": "ragtime-mcp",
      "args": ["--path", "."]
    }
  }
}

The MCP server automatically finds the project root (.ragtime directory) even when Claude is started from a subdirectory.

Available tools:

• remember - Store a memory
• search - Semantic search (supports tiered mode and auto-extraction)
• list_memories - List with filters
• get_memory - Get by ID
• store_doc - Store document verbatim
• forget - Delete memory
• graduate - Promote branch → app
• update_status - Change memory status
• record_feedback - Record when search results are used (improves future rankings)
• feedback_stats - View search result usage patterns

ghp-cli Integration

If you use ghp-cli:

# Register ragtime hooks
ragtime setup-ghp

This auto-creates context.md from issue details when you run ghp start.

Workflow

Starting Work

ghp start 123              # Creates branch + context.md
# or
ragtime new-branch 123     # Just the context

During Development

/remember "API uses rate limiting"   # Capture insights
/handoff                              # Save progress for later

Before PR

/create-pr
# 1. Checks code against CONVENTIONS.md
# 2. Reviews branch memories
# 3. Graduates selected memories to app/
# 4. Commits knowledge with code
# 5. Creates PR

After Merge

Graduated knowledge is already in the PR. Run ragtime prune to clean up synced folders.

License

MIT