Index codebases and documentation, then search them using keyword matching, semantic similarity, graph relationships, or a combination of all three. Supports pluggable embedding and summarization providers (Ollama, OpenAI, Anthropic, Gemini) with per-project configuration and caching.
Search using BM25 keyword matching for exact terms
View embedding cache metrics or clear the cache
12-step wizard to configure all Agent Brain settings — providers, storage, GraphRAG, reranking, caching, file watcher, chunking, and server deployment
Configure the embedding provider for vector search
Manage indexed folders — list, add, or remove
Intelligent research agent that uses Agent Brain for knowledge retrieval with adaptive search modes
Proactively assists with document and code search using Agent Brain
Proactively assists with Agent Brain installation and configuration
Installation and configuration skill for Agent Brain document search system. Use when asked to "install agent brain", "setup agent brain", "configure agent brain", "setting up document search", "installing agent-brain packages", "configuring API keys", "initializing project for search", "troubleshooting agent brain", "pip install agent-brain", "agent brain not working", "agent brain setup error", "configure embeddings provider", "setup ollama for agent brain", or "agent brain environment variables". Covers package installation, provider configuration, project initialization, and server management.
Expert Agent Brain skill for document search with BM25 keyword, semantic vector, hybrid, graph, and multi retrieval modes. Use when asked to "search documentation", "query domain", "find in docs", "bm25 search", "hybrid search", "semantic search", "graph search", "multi search", "find dependencies", "code relationships", "searching knowledge base", "querying indexed documents", "finding code references", "exploring codebase", "what calls this function", "find imports", "trace dependencies", "brain search", "brain query", "knowledge base search", "cache management", "clear embedding cache", "cache hit rate", or "cache status". Supports multi-instance architecture with automatic server discovery. GraphRAG mode enables relationship-aware queries for code dependencies and entity connections. Pluggable providers for embeddings (OpenAI, Cohere, Ollama) and summarization (Anthropic, OpenAI, Gemini, Grok, Ollama). Supports multiple runtimes (Claude Code, OpenCode, Gemini CLI) with shared .agent-brain/ data directory.
Uses power tools
Uses Bash, Write, or Edit tools
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
A RAG-based (Retrieval-Augmented Generation) document indexing and semantic search system for AI agents and applications. Agent Brain enables intelligent querying of documentation and source code using natural language.
Agent Brain provides AI-first document and code search through a Claude Code plugin with skills, commands, and agents. Use slash commands to search, agents for complex research tasks, and skills for intelligent query optimization.
| Component | Description |
|---|---|
| Plugin | 24 slash commands, 3 agents, 2 skills for Claude Code |
| Skills | Intelligent search mode selection and query optimization |
| Agents | Research assistant, search assistant, setup assistant |
| Server | FastAPI backend for indexing and retrieval |
| CLI | Command-line tool (also used by plugin internally) |
claude plugins install github:SpillwaveSolutions/agent-brain
In Claude Code, run:
/agent-brain-setup
This interactive wizard will:
agent-brain-rag, agent-brain-cli)/agent-brain-search "how does authentication work"
That's it! The plugin handles everything automatically.
| Command | Description | Use When |
|---|---|---|
/agent-brain-search | Smart hybrid search (recommended) | General questions |
/agent-brain-semantic | Pure semantic/vector search | Conceptual queries |
/agent-brain-keyword | BM25 keyword search | Error messages, function names |
/agent-brain-hybrid | Hybrid with alpha tuning | Fine-tuned searches |
/agent-brain-graph | Knowledge graph search | "What calls X?", dependencies |
/agent-brain-multi | All modes combined (RRF) | Maximum recall |
| Command | Description |
|---|---|
/agent-brain-start | Start the server (auto-port) |
/agent-brain-stop | Stop the server |
/agent-brain-status | Check health and document count |
/agent-brain-index | Index documents or code |
| Command | Description |
|---|---|
/agent-brain-setup | Complete guided setup wizard |
/agent-brain-install | Install pip packages |
/agent-brain-init | Initialize project directory |
/agent-brain-verify | Verify configuration |
/agent-brain-providers | Configure embedding/summarization providers |
Agent Brain includes three intelligent agents for complex tasks:
| Agent | Description | Triggered By |
|---|---|---|
| Search Assistant | Multi-step search across modes, synthesizes answers | "Find all references to...", "Research how..." |
| Research Assistant | Deep exploration with follow-up queries | "Investigate...", "Analyze the architecture of..." |
| Setup Assistant | Guided installation and troubleshooting | "Help me set up Agent Brain", configuration issues |
You: "Research how authentication is implemented across the codebase"
Research Assistant:
Skills provide intelligent context to Claude for optimal searching:
| Skill | Purpose |
|---|---|
| using-agent-brain | Search mode selection, query optimization, API knowledge |
| configuring-agent-brain | Installation, provider configuration, troubleshooting |
When you ask about documentation or code, Claude automatically uses the skill to:
| Mode | Best For | Example Query |
|---|---|---|
HYBRID | General questions (default) | "How does caching work?" |
VECTOR | Conceptual understanding | "Explain the architecture" |
BM25 | Exact terms, error codes | "NullPointerException", "getUserById" |
GRAPH | Relationships, dependencies | "What classes use AuthService?" |
MULTI | Comprehensive search | "Everything about data validation" |
Agent Brain supports multiple providers for embeddings and summarization:
| Provider | Models | Local |
|---|---|---|
| OpenAI | text-embedding-3-large, text-embedding-3-small | No |
| Ollama | nomic-embed-text, mxbai-embed-large | Yes |
| Cohere | embed-english-v3.0, embed-multilingual-v3.0 | No |
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