Node.js wrapper for the probe code search tool
npm install @probelabs/probeA Node.js wrapper for the probe code search tool.
``bash`
npm install @probelabs/probe
`bash`
npm install -g @probelabs/probe
During installation, the package will automatically download the appropriate probe binary for your platform.
- Search Code: Search for patterns in your codebase using Elasticsearch-like query syntax
- Query Code: Find specific code structures using tree-sitter patterns
- Extract Code: Extract code blocks from files based on file paths and line numbers
- AI Tools Integration: Ready-to-use tools for Vercel AI SDK, LangChain, and other AI frameworks
- System Message: Default system message for AI assistants with instructions on using probe tools
- Cross-Platform: Works on Windows, macOS, and Linux
- Automatic Binary Management: Automatically downloads and manages the probe binary
- Direct CLI Access: Use the probe binary directly from the command line when installed globally
- MCP Server: Built-in Model Context Protocol server for AI assistant integration
- Context Window Compaction: Automatic conversation history compression when approaching token limits
`javascript
import { search, query, extract } from '@probelabs/probe';
// Search for code
const searchResults = await search({
path: '/path/to/your/project',
query: 'function',
maxResults: 10
});
// Query for specific code structures
const queryResults = await query({
path: '/path/to/your/project',
pattern: 'function $NAME($$$PARAMS) $$$BODY',
language: 'javascript'
});
// Extract code blocks
const extractResults = await extract({
files: ['/path/to/your/project/src/main.js:42']
});
`
When installed globally, the probe command will be available directly from the command line:
`bashSearch for code
probe search "function" /path/to/your/project
The package installs the actual probe binary, not a JavaScript wrapper, so you get the full native performance and all features of the original probe CLI.
$3
ProbeAgent provides a high-level AI-powered interface for interacting with your codebase:
javascript
import { ProbeAgent } from '@probelabs/probe';// Create an AI agent for your project
const agent = new ProbeAgent({
sessionId: 'my-session', // Optional: for conversation continuity
path: '/path/to/your/project',
provider: 'anthropic', // or 'openai', 'google'
model: 'claude-3-5-sonnet-20241022', // Optional: override model
allowEdit: false, // Optional: enable code modification
debug: true, // Optional: enable debug logging
allowedTools: ['*'], // Optional: filter available tools (see Tool Filtering below)
enableMcp: true, // Optional: enable MCP tool integration
mcpConfig: { // Optional: MCP configuration (see MCP section below)
mcpServers: {...}
}
});
// Ask questions about your codebase
const answer = await agent.answer("How does authentication work in this codebase?");
console.log(answer);
// The agent maintains conversation history automatically
const followUp = await agent.answer("Can you show me the login implementation?");
console.log(followUp);
// Get token usage statistics
const usage = agent.getTokenUsage();
console.log(
Used ${usage.total} tokens total);// Clear conversation history if needed
agent.history = [];
`Environment Variables:
bash
Set your API key for the chosen provider
export ANTHROPIC_API_KEY=your_anthropic_key
export OPENAI_API_KEY=your_openai_key
export GOOGLE_API_KEY=your_google_keyOptional: Force a specific provider
export FORCE_PROVIDER=anthropicOptional: Override model name
export MODEL_NAME=claude-3-5-sonnet-20241022
`ProbeAgent Features:
- Multi-turn conversations with automatic history management
- Code search integration - Uses probe's search capabilities transparently
- Multiple AI providers - Supports Anthropic Claude, OpenAI GPT, Google Gemini, AWS Bedrock
- Automatic retry with exponential backoff - Handles transient API failures gracefully
- Provider fallback - Seamlessly switch between providers if one fails (e.g., Azure Claude → Bedrock Claude → OpenAI)
- Session management - Maintain conversation context across calls
- Token tracking - Monitor usage and costs
- Configurable personas - Engineer, architect, code-review, and more
$3
ProbeAgent can discover and activate Agent Skills stored inside your repository. Place skills under:
-
-
-
- should contain YAML frontmatter followed by Markdown instructions. Example:`markdown
---
name: onboarding
description: Help new engineers understand the repo structure and conventions.
---Use this skill to explain key modules, build steps, and common workflows.
`Then in the agent loop you can call:
xml
`
or:
xml
onboarding
`$3
ProbeAgent includes comprehensive retry and fallback capabilities for maximum reliability:
javascript
import { ProbeAgent } from '@probelabs/probe';const agent = new ProbeAgent({
path: '/path/to/your/project',
// Configure retry behavior
retry: {
maxRetries: 5, // Retry up to 5 times per provider
initialDelay: 1000, // Start with 1 second delay
maxDelay: 30000, // Cap delays at 30 seconds
backoffFactor: 2 // Double the delay each time
},
// Configure provider fallback
fallback: {
strategy: 'custom',
providers: [
{
provider: 'anthropic',
apiKey: process.env.ANTHROPIC_API_KEY,
model: 'claude-3-7-sonnet-20250219',
maxRetries: 5 // Can override retry config per provider
},
{
provider: 'bedrock',
region: 'us-west-2',
accessKeyId: process.env.AWS_ACCESS_KEY_ID,
secretAccessKey: process.env.AWS_SECRET_ACCESS_KEY,
model: 'anthropic.claude-sonnet-4-20250514-v1:0'
},
{
provider: 'openai',
apiKey: process.env.OPENAI_API_KEY,
model: 'gpt-4o'
}
],
maxTotalAttempts: 15 // Maximum attempts across all providers
}
});
// API calls automatically retry on failures and fallback to other providers
const answer = await agent.answer("Explain this codebase");
`Retry & Fallback Features:
- Exponential backoff - Intelligently delays retries to avoid overwhelming APIs
- Automatic error detection - Retries on transient errors (Overloaded, 429, 503, timeouts, network errors)
- Multi-provider support - Fallback across Anthropic, OpenAI, Google, and AWS Bedrock
- Cross-cloud failover - Use Azure Claude → Bedrock Claude → OpenAI as fallback chain
- Statistics tracking - Monitor retry attempts and provider usage
- Environment variable support - Configure via env vars for easy deployment
Quick Setup with Auto-Fallback:
bash
Set all your API keys
export ANTHROPIC_API_KEY=sk-ant-xxx
export OPENAI_API_KEY=sk-xxx
export GOOGLE_API_KEY=xxx
export AUTO_FALLBACK=1 # Enable automatic fallback
export MAX_RETRIES=5 # Configure retry limit
`javascript
// No configuration needed - uses all available providers automatically!
const agent = new ProbeAgent({
path: '/path/to/your/project',
fallback: { auto: true }
});
`See docs/RETRY_AND_FALLBACK.md for complete documentation and examples.
$3
ProbeAgent supports filtering available tools to control what operations the AI can perform. This is useful for security, cost control, or limiting functionality to specific use cases.
javascript
import { ProbeAgent } from '@probelabs/probe';// Allow all tools (default behavior)
const agent1 = new ProbeAgent({
path: '/path/to/project',
allowedTools: ['*'] // or undefined
});
// Allow only specific tools (whitelist mode)
const agent2 = new ProbeAgent({
path: '/path/to/project',
allowedTools: ['search', 'query', 'extract']
});
// Allow all except specific tools (exclusion mode)
const agent3 = new ProbeAgent({
path: '/path/to/project',
allowedTools: ['*', '!bash', '!implement']
});
// Raw AI mode - no tools at all
const agent4 = new ProbeAgent({
path: '/path/to/project',
allowedTools: [] // or use disableTools: true
});
// Convenience flag for raw AI mode (better DX)
const agent5 = new ProbeAgent({
path: '/path/to/project',
disableTools: true // Clearer than allowedTools: []
});
`Available Tools:
-
- Semantic code search
- query - Tree-sitter pattern matching
- extract - Extract code blocks
- listFiles - List files and directories
- searchFiles - Find files by glob pattern
- bash - Execute bash commands (requires enableBash: true)
- implement - Implement features with aider (requires allowEdit: true)
- edit - Edit files with exact string replacement (requires allowEdit: true)
- create - Create new files (requires allowEdit: true)
- delegate - Delegate tasks to subagents (requires enableDelegate: true)
- attempt_completion - Signal task completion
- mcp__* - MCP tools use the mcp__ prefix (e.g., mcp__filesystem__read_file)MCP Tool Filtering:
MCP tools follow the
mcp__toolname naming convention. You can:
- Allow all MCP tools: allowedTools: ['*']
- Allow specific MCP tool:
- Allow all from a server: (using pattern matching)
- Block MCP tools: allowedTools: ['', '!mcp__']CLI Usage:
bash
Allow only search and extract tools
probe agent "Explain this code" --allowed-tools search,extractRaw AI mode (no tools) - option 1
probe agent "What is this project about?" --allowed-tools noneRaw AI mode (no tools) - option 2 (better DX)
probe agent "Tell me about this project" --disable-toolsAll tools (default)
probe agent "Analyze the architecture" --allowed-tools all
`Notes:
- Tool filtering works in conjunction with feature flags (
, enableBash, enableDelegate)
- Both the feature flag AND allowedTools must permit a tool for it to be available
- Blocked tools will not appear in the system message and cannot be executed
- Use allowedTools: [] for pure conversational AI without code analysis tools$3
Probe includes a built-in MCP (Model Context Protocol) server for integration with AI assistants:
`bash
Start the MCP server
probe mcpWith custom timeout
probe mcp --timeout 60
`Add to your AI assistant's MCP configuration:
json
{
"mcpServers": {
"probe": {
"command": "npx",
"args": ["-y", "@probelabs/probe", "mcp"]
}
}
}
`$3
When using ProbeAgent programmatically, you can integrate MCP servers to extend the agent's capabilities:
javascript
const agent = new ProbeAgent({
enableMcp: true, // Enable MCP support // Option 1: Provide MCP configuration directly
mcpConfig: {
mcpServers: {
'my-server': {
command: 'node',
args: ['path/to/server.js'],
transport: 'stdio',
enabled: true
}
}
},
// Option 2: Load from config file
mcpConfigPath: '/path/to/mcp-config.json',
// Option 3: Auto-discovery from standard locations
// (~/.mcp/config.json, or via MCP_CONFIG_PATH env var)
});
`Note: MCP tools are automatically initialized when needed (lazy initialization), so you don't need to call
when using the SDK.Claude Code Integration
ProbeAgent now supports Claude Code's
claude command for zero-configuration usage in Claude Code environments. See the Claude Code Integration Guide for full details.$3
`javascript
import { ProbeAgent } from '@probelabs/probe';// Works automatically if claude command is installed!
const agent = new ProbeAgent({
allowedFolders: ['/path/to/your/code']
});
await agent.initialize();
const response = await agent.answer('Explain how this codebase works');
`$3
ProbeAgent automatically detects and uses Claude Code when:
- No API keys are configured (no ANTHROPIC_API_KEY, OPENAI_API_KEY, etc.)
- The
command is available on your systemPriority order:
1. Explicit
provider: 'claude-code'
2. API keys (Anthropic, OpenAI, Google, AWS)
3. Claude command (auto-detected)$3
- Zero Configuration: No API keys needed in Claude Code environments
- Black-box Operation: Claude Code handles its own agentic loop
- Tool Event Extraction: Visibility into internal tool usage
- Built-in MCP Server: Provides Probe's semantic search tools
- Auto-fallback: Seamlessly switches based on environment
For complete documentation, examples, and troubleshooting, see docs/CLAUDE_CODE_INTEGRATION.md.
API Reference
$3
javascript
import { search } from '@probelabs/probe';const results = await search({
path: '/path/to/your/project',
query: 'function',
// Optional parameters
filesOnly: false,
ignore: ['node_modules', 'dist'],
excludeFilenames: false,
reranker: 'hybrid',
frequencySearch: true,
maxResults: 10,
maxBytes: 1000000,
maxTokens: 40000,
allowTests: false,
noMerge: false,
mergeThreshold: 5,
json: false,
binaryOptions: {
forceDownload: false,
version: '1.0.0'
}
});
`#### Parameters
-
(required): Path to search in
- query (required): Search query or queries (string or array of strings)
- filesOnly: Only output file paths
- ignore: Patterns to ignore (array of strings)
- excludeFilenames: Exclude filenames from search
- reranker: Reranking method ('hybrid', 'hybrid2', 'bm25', 'tfidf')
- frequencySearch: Use frequency-based search
- maxResults: Maximum number of results
- maxBytes: Maximum bytes to return
- maxTokens: Maximum tokens to return
- allowTests: Include test files
- noMerge: Don't merge adjacent blocks
- mergeThreshold: Merge threshold
- json: Return results as parsed JSON instead of string
- binaryOptions: Options for getting the binary
- forceDownload: Force download even if binary exists
- version: Specific version to download$3
`javascript
import { query } from '@probelabs/probe';const results = await query({
path: '/path/to/your/project',
pattern: 'function $NAME($$$PARAMS) $$$BODY',
// Optional parameters
language: 'javascript',
ignore: ['node_modules', 'dist'],
allowTests: false,
maxResults: 10,
format: 'markdown',
json: false,
binaryOptions: {
forceDownload: false,
version: '1.0.0'
}
});
`#### Parameters
-
(required): Path to search in
- pattern (required): The ast-grep pattern to search for
- language: Programming language to search in
- ignore: Patterns to ignore (array of strings)
- allowTests: Include test files
- maxResults: Maximum number of results
- format: Output format ('markdown', 'plain', 'json', 'color')
- json: Return results as parsed JSON instead of string
- binaryOptions: Options for getting the binary
- forceDownload: Force download even if binary exists
- version: Specific version to download$3
`javascript
import { extract } from '@probelabs/probe';const results = await extract({
files: [
'/path/to/your/project/src/main.js',
'/path/to/your/project/src/utils.js:42' // Extract from line 42
],
// Optional parameters
allowTests: false,
contextLines: 2,
format: 'markdown',
json: false,
binaryOptions: {
forceDownload: false,
version: '1.0.0'
}
});
`#### Parameters
-
(required): Files to extract from (can include line numbers with colon, e.g., "/path/to/file.rs:10")
- allowTests: Include test files
- contextLines: Number of context lines to include
- format: Output format ('markdown', 'plain', 'json')
- json: Return results as parsed JSON instead of string
- binaryOptions: Options for getting the binary
- forceDownload: Force download even if binary exists
- version: Specific version to download$3
`javascript
import { getBinaryPath, setBinaryPath } from '@probelabs/probe';// Get the path to the probe binary
const binaryPath = await getBinaryPath({
forceDownload: false,
version: '1.0.0'
});
// Manually set the path to the probe binary
setBinaryPath('/path/to/probe/binary');
`$3
javascript
import { tools } from '@probelabs/probe';// Vercel AI SDK tools
const { searchTool, queryTool, extractTool } = tools;
// LangChain tools
const searchLangChainTool = tools.createSearchTool();
const queryLangChainTool = tools.createQueryTool();
const extractLangChainTool = tools.createExtractTool();
// Access schemas
const { searchSchema, querySchema, extractSchema } = tools;
// Access default system message
const systemMessage = tools.DEFAULT_SYSTEM_MESSAGE;
`#### Vercel AI SDK Tools
-
: Tool for searching code using Elasticsearch-like query syntax
- queryTool: Tool for searching code using tree-sitter patterns
- extractTool: Tool for extracting code blocks from files#### LangChain Tools
-
createSearchTool(): Creates a tool for searching code using Elasticsearch-like query syntax
- createQueryTool(): Creates a tool for searching code using tree-sitter patterns
- createExtractTool(): Creates a tool for extracting code blocks from files#### Schemas
-
searchSchema: Zod schema for search tool parameters
- querySchema: Zod schema for query tool parameters
- extractSchema: Zod schema for extract tool parameters#### System Message
-
DEFAULT_SYSTEM_MESSAGE: Default system message for AI assistants with instructions on how to use the probe tools
- extractSchema: Zod schema for extract tool parametersExamples
$3
`javascript
import { search } from '@probelabs/probe';async function basicSearchExample() {
try {
const results = await search({
path: '/path/to/your/project',
query: 'function',
maxResults: 5
});
console.log('Search results:');
console.log(results);
} catch (error) {
console.error('Search error:', error);
}
}
`$3
javascript
import { search } from '@probelabs/probe';async function advancedSearchExample() {
try {
const results = await search({
path: '/path/to/your/project',
query: 'config AND (parse OR tokenize)',
ignore: ['node_modules', 'dist'],
reranker: 'hybrid',
frequencySearch: true,
maxResults: 10,
maxTokens: 20000,
allowTests: false
});
console.log('Advanced search results:');
console.log(results);
} catch (error) {
console.error('Advanced search error:', error);
}
}
`$3
javascript
import { query } from '@probelabs/probe';async function queryExample() {
try {
// Find all JavaScript functions
const jsResults = await query({
path: '/path/to/your/project',
pattern: 'function $NAME($$$PARAMS) $$$BODY',
language: 'javascript',
maxResults: 5
});
console.log('JavaScript functions:');
console.log(jsResults);
// Find all Rust structs
const rustResults = await query({
path: '/path/to/your/project',
pattern: 'struct $NAME $$$BODY',
language: 'rust',
maxResults: 5
});
console.log('Rust structs:');
console.log(rustResults);
} catch (error) {
console.error('Query error:', error);
}
}
`$3
javascript
import { extract } from '@probelabs/probe';async function extractExample() {
try {
const results = await extract({
files: [
'/path/to/your/project/src/main.js',
'/path/to/your/project/src/utils.js:42' // Extract from line 42
],
contextLines: 2,
format: 'markdown'
});
console.log('Extracted code:');
console.log(results);
} catch (error) {
console.error('Extract error:', error);
}
}
`How It Works
When you install this package:
1. A placeholder binary is included in the package
2. During installation, the postinstall script downloads the actual probe binary for your platform
3. The placeholder is replaced with the actual binary
4. When installed globally, npm creates a symlink to this binary in your system path
This approach ensures that you get the actual native binary, not a JavaScript wrapper, providing full performance and all features of the original probe CLI.
AI Tools Integration
The package provides built-in tools for integrating with AI SDKs like Vercel AI SDK and LangChain, allowing you to use probe's powerful code search capabilities in AI applications.
$3
javascript
import { generateText } from 'ai';
import { tools } from '@probelabs/probe';// Use the pre-built tools with Vercel AI SDK
async function chatWithAI(userMessage) {
const result = await generateText({
model: provider(modelName),
messages: [{ role: 'user', content: userMessage }],
system: "You are a code intelligence assistant. Use the provided tools to search and analyze code.",
tools: {
search: tools.searchTool,
query: tools.queryTool,
extract: tools.extractTool
},
maxSteps: 15,
temperature: 0.7
});
return result.text;
}
`$3
javascript
import { ChatOpenAI } from '@langchain/openai';
import { tools } from '@probelabs/probe';// Create the LangChain tools
const searchTool = tools.createSearchTool();
const queryTool = tools.createQueryTool();
const extractTool = tools.createExtractTool();
// Create a ChatOpenAI instance with tools
const model = new ChatOpenAI({
modelName: "gpt-4o",
temperature: 0.7
}).withTools([searchTool, queryTool, extractTool]);
// Use the model with tools
async function chatWithAI(userMessage) {
const result = await model.invoke([
{ role: "system", content: "You are a code intelligence assistant. Use the provided tools to search and analyze code." },
{ role: "user", content: userMessage }
]);
return result.content;
}
`$3
The package provides a default system message that you can use with your AI assistants:
javascript
import { tools } from '@probelabs/probe';// Use the default system message in your AI application
const systemMessage = tools.DEFAULT_SYSTEM_MESSAGE;
// Example with Vercel AI SDK
const result = await generateText({
model: provider(modelName),
messages: [{ role: 'user', content: userMessage }],
system: tools.DEFAULT_SYSTEM_MESSAGE,
tools: {
search: tools.searchTool,
query: tools.queryTool,
extract: tools.extractTool
}
});
`The default system message provides instructions for AI assistants on how to use the probe tools effectively, including search query formatting, tool execution sequence, and best practices.
License
ISC
Migration from @probelabs/probe-mcp
If you're migrating from the standalone
package, probe mcp is a drop-in replacement:Old usage:
`bash
npx @probelabs/probe-mcp
or
probe-mcp --timeout 60
`New usage (drop-in replacement):
bash
probe mcp
or
probe mcp --timeout 60
`MCP Configuration:
json
// Old configuration
{
"mcpServers": {
"probe": {
"command": "npx",
"args": ["-y", "@probelabs/probe-mcp"]
}
}
}// New configuration (drop-in replacement)
{
"mcpServers": {
"probe": {
"command": "npx",
"args": ["-y", "@probelabs/probe", "mcp"]
}
}
}
``- Context Window Compaction - Automatic conversation history compression
- MCP Integration - Model Context Protocol support details
- Delegate Tool - Task distribution to subagents
- Maid Integration - Integration with Maid LLM framework
- probe - The core probe code search tool