VibeScout
Provides integration with Cloudflare Vectorize for vector storage and Workers AI for cloud-based embeddings and AI inference.
Enables use of local AI models via Ollama for embeddings and chat completion.
Allows using OpenAI or compatible APIs for embeddings and chat, supporting models like GPT and embeddings.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@VibeScoutfind the user authentication function"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
VibeScout: Local Code Intelligence & MCP Server
A high-performance Model Context Protocol (MCP) server and Web Dashboard for local semantic code search and AI-powered assistance. VibeScout transforms your codebase into a searchable, chat-ready knowledge base using local or cloud-based AI providers.
π Features
Core Capabilities
Web Dashboard: A modern React-based UI for visual searching, chatting with your code, and managing your knowledge base.
Semantic Code Search: Fast vector-based search with BGE reranking for extreme technical accuracy.
Visual Dependency Graph: Explore architecture visually with Symbol Intelligence panel and Circular Dependency Detection.
AI-Powered Chat: Persistent context chat with RAG-powered code understanding.
Real-time File Watching: Automatic re-indexing when files change (chokidar-based).
Search & Filtering
Category Pre-Filtering: Database-level filtering by Code/Docs for maximum performance (default: Code-only).
Token Count Preview: Preview search results before consuming tokens with two-phase search (MCP only).
Git Metadata: Enhanced search with author, date, churn level, and commit history.
Dependencies Display: View imports/exports for each search result with source tracking.
Search Persistence: Results persist across tab switches for seamless workflow.
Framework Detection: Auto-detects Next.js, React Router, Vue, Angular, and 10+ frameworks.
Plugin System
Modular Architecture: Built-in, npm, and local plugin support with override detection.
Versioned Structure:
/src/plugins/<name>/<version>/for built-in plugins.Compatibility Checking: Auto-disables incompatible plugins with clear warnings.
Runtime Toggle: Enable/disable plugins via UI or config file.
Sandboxed Execution: Isolated worker threads for safe plugin operation.
Advanced Features
Two-Phase Search: Preview search metadata before consuming tokens (MCP only).
AI Smart Questions: "Generate Best Question" analyzes code to suggest optimal chat starting points.
Adaptive Concurrency: Automatically detects provider rate limits and dynamically scales request rates.
Real-time Activity (SSE): Instant system event streaming via Server-Sent Events.
AI Inspector (Debug): Chrome DevTools-style panel to inspect prompts, payloads, and responses.
IDE Integration: "Open in Editor" with line-level navigation for VS Code and Cursor.
Performance Profiling: Built-in profiling with Chrome DevTools flame graphs for optimizing indexing and search performance.
Technical Stack
Hono-Powered Backend: Ultra-low latency with standard Web Fetch API support.
Multi-Language Support: TypeScript/JS, Python, Go, Java, Kotlin, Dart, Markdown, JSON, TOML, XML.
Hybrid Storage: Local LanceDB or Cloudflare Vectorize for cloud embeddings.
AI Reranker: Optional second-pass re-sorting with local models.
Fully Offline Mode: Strict local-only operation, no remote model downloads.
Related MCP server: Portable MCP Toolkit
π€ Supported Providers
Provider | Type | Description |
Local | Built-in | Transformers.js (BGE, MiniLM). High-speed, zero config. |
Ollama | Local API | Full support for local models like Llama 3, Mistral, and Nomic. |
Z.AI | Cloud | BigModel.cn integration. Supports GLM-4 and dedicated Coding Plans. |
Bedrock | Cloud | AWS Bedrock (Claude 3, Titan). Supports AWS Profiles. |
Gemini | Cloud | Google Generative AI (1.5 Flash/Pro) and specialized embeddings. |
OpenAI | Cloud | Standard OpenAI API or compatible (DeepSeek, Groq, etc). |
Cloudflare | Cloud | Workers AI & Vectorize integration for cloud-native indexing. |
LM Studio | Local API | OpenAI-compatible local server preset. |
π Plugin System
VibeScout features a powerful plugin system for extending functionality:
Plugin Sources
Built-in Plugins: Shipped with VibeScout (
/src/plugins/<name>/<version>/)npm Packages: Install via
vibescout plugin install <name>Local Plugins: Place in
~/.vibescout/plugins/
Plugin Capabilities
Extractors: Custom code extraction strategies (e.g., framework-specific metadata)
Providers: Custom embedding/summarizer providers
Commands: CLI commands for framework-specific operations
Plugin Management
# List plugins
vibescout plugin list
# Install from npm
vibescout plugin install vibescout-plugin-nextjs
# Install specific version
vibescout plugin install vibescout-plugin-nextjs@beta
# Uninstall
vibescout plugin uninstall vibescout-plugin-nextjs
# Enable/Disable (via Web UI or config.json)
# Plugins are stored in ~/.vibescout/config.jsonPlugin Development
See /docs/ directory for:
plugin-guide.md- Getting startedplugin-api.md- API referenceplugin-architecture.md- Design patternsplugin-example.md- Complete exampletwo-phase-search.md- Two-phase search with token count previewprofiling-guide.md- Performance profiling and optimization
π Installation
Global Installation
npm install -g @sevenseconds/vibescoutπ» CLI Usage
Web UI
Launch the interactive dashboard:
vibescout uiAdvanced Logging
Control terminal output verbosity:
# Default is INFO (concise)
vibescout ui --log-level warn
# Full debug output (alias for --log-level debug)
vibescout ui --verboseIndexing & Search
# Index a project manually
vibescout index ./my-app "My Project"
# Semantic search via terminal
vibescout search "how does the auth flow work?"
# Reset the database (clear all data)
vibescout reset
# Or via npm
npm run reset-dbTwo-Phase Search (MCP Only)
When using VibeScout with Claude Desktop, Cursor, or other MCP clients, you can preview search results before consuming tokens:
Phase 1: Preview Token Count
{
"name": "search_code",
"arguments": {
"query": "authentication flow",
"limit": 20,
"previewOnly": true
}
}This returns metadata without actual code:
Result count
Total tokens (from stored counts during indexing)
Average relevance score
Recommendation on whether to proceed
Phase 2: Fetch Results (if tokens are acceptable)
{
"name": "search_code",
"arguments": {
"query": "authentication flow",
"limit": 10,
"previewOnly": false
}
}Benefits:
Avoid unexpected token consumption
Adjust
limitparameter based on previewUse more specific filters if token count is high
Backward compatible: omit
previewOnlyfor existing behavior
Performance Profiling
# Profile with 100% sampling (most detailed)
vibescout --profile index ./my-app "My Project"
# Profile with 10% sampling (lower overhead)
vibescout --profile --profile-sampling 0.1 search "authentication"
# Dedicated profiling command
vibescout profile index --folder ./my-app --sampling 1.0
# View traces in chrome://tracing
# Traces saved to ~/.vibescout/profiles/Profiling Features:
Zero overhead when disabled (default)
Chrome DevTools-compatible flame graphs
Configurable sampling rates (0.0-1.0) to reduce overhead
Category-based sampling (indexing, search, embedding, database)
Web UI dashboard at http://localhost:3000/performance
See docs/profiling-guide.md for detailed documentation.
π Offline Mode
To use VibeScout in a restricted environment without internet access:
Download Models: In an online environment, let VibeScout download the models first, or download them manually from Hugging Face.
Enable Offline Mode: Toggle Offline Mode in Settings or run with the
--offlineflag.Local Path: Use
--models-path <path>if your models are stored in a non-standard directory.
When enabled, VibeScout sets allowRemoteModels: false and disables all attempts to connect to the Hugging Face Hub.
π Client Integration
Claude Desktop / Gemini CLI
Add VibeScout to your configuration:
{
"mcpServers": {
"vibescout": {
"command": "vibescout",
"args": ["--mcp", "stdio"]
}
}
}π License
MIT License. See LICENSE for details.
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