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AI-friendly semantic code search engine for large codebases. Combines ripgrep speed with tree-sitter AST parsing. Powers AI coding assistants with precise, context-aware code understanding.

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Probe Logo

Probe

We read code 10x more than we write it. Probe is a code and markdown context engine, with a built-in agent, made to work on enterprise-scale codebases.

Today's AI coding tools use a caveman approach: grep some files, read random lines, hope for the best. It works on toy projects. It falls apart on real codebases.

Probe is a context engine built for reading and reasoning. It treats your code as code—not text. AST parsing understands structure. Semantic search finds what matters. You get complete, meaningful context in a single call.

The Probe Agent is purpose-built for code understanding. It knows how to wield the Probe engine expertly—searching, extracting, and reasoning across your entire codebase. Perfect for spec-driven development, code reviews, onboarding, and any task where understanding comes before writing.

One Probe call captures what takes other tools 10+ agentic loops—deeper, cleaner, and far less noise.


Why Probe?

Traditional Approach Probe
Grep + read random lines Semantic search with Elasticsearch syntax
Treats code as text Understands code structure via tree-sitter AST
Returns fragments Returns complete functions, classes, structs
Requires indexing Zero setup, instant results
10+ loops to gather context One call, complete picture
Struggles at scale Built for million-line codebases

Quick Start

Option 1: Probe Agent via MCP (Recommended)

Our built-in agent natively integrates with Claude Code, using its authentication—no extra API keys needed.

Add to ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "probe": {
      "command": "npx",
      "args": ["-y", "@probelabs/probe@latest", "agent", "--mcp"]
    }
  }
}

The Probe Agent is purpose-built to read and reason about code. It piggybacks on Claude Code's auth (or Codex auth), or works with any model via your own API key (e.g., GOOGLE_API_KEY).

Option 2: Raw Probe Tools via MCP

If you prefer direct access to search/query/extract tools without the agent layer:

{
  "mcpServers": {
    "probe": {
      "command": "npx",
      "args": ["-y", "@probelabs/probe@latest", "mcp"]
    }
  }
}

Option 3: Direct CLI (No MCP)

Use Probe directly from your terminal—no AI editor required:

# Semantic search with Elasticsearch syntax
npx -y @probelabs/probe search "authentication AND login" ./src

# Extract code block at line 42
npx -y @probelabs/probe extract src/main.rs:42

# AST pattern matching
npx -y @probelabs/probe query "fn $NAME($$$) -> Result<$RET>" --language rust

Option 4: CLI Agent

Ask questions about any codebase directly from your terminal:

# One-shot question (works with any LLM provider)
npx -y @probelabs/probe@latest agent "How is authentication implemented?"

# With code editing capabilities
npx -y @probelabs/probe@latest agent "Refactor the login function" --allow-edit

Table of Contents


Features

  • Code-Aware: Tree-sitter AST parsing understands your code's actual structure
  • Semantic Search: Elasticsearch-style queries (AND, OR, NOT, phrases, filters)
  • Complete Context: Returns entire functions, classes, or structs—not fragments
  • One Call, Full Context: Captures what takes other tools 10+ loops to gather
  • Zero Indexing: Instant results on any codebase, no setup required
  • Fully Local: Your code never leaves your machine
  • Blazing Fast: Ripgrep-powered scanning handles million-line codebases
  • Smart Ranking: BM25, TF-IDF, and hybrid algorithms surface what matters
  • Multi-Language: Rust, Python, JavaScript, TypeScript, Go, C/C++, Java, and more

Usage Modes

Probe Agent (MCP)

The recommended way to use Probe with AI editors. The Probe Agent is a specialized coding assistant that reasons about your code—not just pattern matches.

{
  "mcpServers": {
    "probe": {
      "command": "npx",
      "args": ["-y", "@probelabs/probe@latest", "agent", "--mcp"]
    }
  }
}

Why use the agent?

  • Purpose-built to understand and reason about code
  • Piggybacks on Claude Code / Codex authentication (or use your own API key)
  • Smarter multi-step reasoning for complex questions
  • Built-in code editing, task delegation, and more

Agent options:

Option Description
--path <dir> Search directory (default: current)
--provider <name> AI provider: anthropic, openai, google
--model <name> Override model name
--prompt <type> Persona: code-explorer, engineer, code-review, architect
--allow-edit Enable code modification
--enable-delegate Enable task delegation to subagents
--enable-bash Enable bash command execution
--max-iterations <n> Max tool iterations (default: 30)

Raw MCP Tools

Direct access to Probe's search, query, and extract tools—without the agent layer. Use this when you want your AI editor to call Probe tools directly.

{
  "mcpServers": {
    "probe": {
      "command": "npx",
      "args": ["-y", "@probelabs/probe@latest", "mcp"]
    }
  }
}

Available tools:

  • search - Semantic code search with Elasticsearch-style queries
  • query - AST-based structural pattern matching
  • extract - Extract code blocks by line number or symbol name

CLI Agent

Run the Probe Agent directly from your terminal:

# One-shot question
npx -y @probelabs/probe@latest agent "How does the ranking algorithm work?"

# Specify search path
npx -y @probelabs/probe@latest agent "Find API endpoints" --path ./src

# Enable code editing
npx -y @probelabs/probe@latest agent "Add error handling to login()" --allow-edit

# Use custom persona
npx -y @probelabs/probe@latest agent "Review this code" --prompt code-review

Direct CLI Commands

For scripting and direct code analysis.

Search Command

probe search <PATTERN> [PATH] [OPTIONS]

Examples:

# Basic search
probe search "authentication" ./src

# Boolean operators (Elasticsearch syntax)
probe search "error AND handling" ./
probe search "login OR auth" ./src
probe search "database NOT sqlite" ./

# Search hints (file filters)
probe search "function AND ext:rs" ./           # Only .rs files
probe search "class AND file:src/**/*.py" ./    # Python files in src/
probe search "error AND dir:tests" ./           # Files in tests/

# Limit results for AI context windows
probe search "API" ./ --max-tokens 10000

Key options:

Option Description
--max-tokens <n> Limit total tokens returned
--max-results <n> Limit number of results
--reranker <algo> Ranking: bm25, tfidf, hybrid, hybrid2
--allow-tests Include test files
--format <fmt> Output: markdown, json, xml

Extract Command

probe extract <FILES> [OPTIONS]

Examples:

# Extract function at line 42
probe extract src/main.rs:42

# Extract by symbol name
probe extract src/main.rs#authenticate

# Extract line range
probe extract src/main.rs:10-50

# From compiler output
go test | probe extract

Query Command (AST Patterns)

probe query <PATTERN> [PATH] [OPTIONS]

Examples:

# Find all async functions in Rust
probe query "async fn $NAME($$$)" --language rust

# Find React components
probe query "function $NAME($$$) { return <$$$> }" --language javascript

# Find Python classes with specific method
probe query "class $CLASS: def __init__($$$)" --language python

Node.js SDK

Use Probe programmatically in your applications.

import { ProbeAgent } from '@probelabs/probe/agent';

// Create agent
const agent = new ProbeAgent({
  path: './src',
  provider: 'anthropic'
});

await agent.initialize();

// Ask questions
const response = await agent.answer('How does authentication work?');
console.log(response);

// Get token usage
console.log(agent.getTokenUsage());

Direct functions:

import { search, extract, query } from '@probelabs/probe';

// Semantic search
const results = await search({
  query: 'authentication',
  path: './src',
  maxTokens: 10000
});

// Extract code
const code = await extract({
  files: ['src/auth.ts:42'],
  format: 'markdown'
});

// AST pattern query
const matches = await query({
  pattern: 'async function $NAME($$$)',
  path: './src',
  language: 'typescript'
});

Vercel AI SDK integration:

import { tools } from '@probelabs/probe';

const { searchTool, queryTool, extractTool } = tools;

// Use with Vercel AI SDK
const result = await generateText({
  model: anthropic('claude-sonnet-4-5-20250929'),
  tools: {
    search: searchTool({ defaultPath: './src' }),
    query: queryTool({ defaultPath: './src' }),
    extract: extractTool({ defaultPath: './src' })
  },
  prompt: 'Find authentication code'
});

Installation

NPM (Recommended)

npm install -g @probelabs/probe

curl (macOS/Linux)

curl -fsSL https://raw.githubusercontent.com/probelabs/probe/main/install.sh | bash

PowerShell (Windows)

iwr -useb https://raw.githubusercontent.com/probelabs/probe/main/install.ps1 | iex

From Source

git clone https://github.com/probelabs/probe.git
cd probe
cargo build --release
cargo install --path .

Supported Languages

Language Extensions
Rust .rs
JavaScript/JSX .js, .jsx
TypeScript/TSX .ts, .tsx
Python .py
Go .go
C/C++ .c, .h, .cpp, .cc, .hpp
Java .java
Ruby .rb
PHP .php
Swift .swift
C# .cs
Markdown .md

Documentation

Getting Started

Probe CLI

Probe Agent

Guides & Reference


Environment Variables

# AI Provider Keys
ANTHROPIC_API_KEY=sk-ant-...
OPENAI_API_KEY=sk-...
GOOGLE_API_KEY=...

# Provider Selection
FORCE_PROVIDER=anthropic
MODEL_NAME=claude-sonnet-4-5-20250929

# Custom Endpoints
ANTHROPIC_API_URL=https://your-proxy.com
OPENAI_API_URL=https://your-proxy.com

# Debug
DEBUG=1

Contributing

We welcome contributions! See our Contributing Guide.

For questions or support:


License

Apache 2.0 - See LICENSE for details.

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AI-friendly semantic code search engine for large codebases. Combines ripgrep speed with tree-sitter AST parsing. Powers AI coding assistants with precise, context-aware code understanding.

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