open-agent-sdk
Open Agent SDK
Skill by ara.so — Daily 2026 Skills collection.
Open Agent SDK (@shipany/open-agent-sdk) is a fully open-source, in-process AI agent framework for TypeScript/Node.js. It runs the complete Claude Code agent engine directly — no local CLI subprocess required — making it suitable for cloud servers, serverless functions, Docker containers, and CI/CD pipelines. It is API-compatible with @anthropic-ai/claude-agent-sdk.
Installation
npm install @shipany/open-agent-sdk
Requires Node.js 18+.
Authentication & Configuration
Set the Anthropic API key as an environment variable:
export ANTHROPIC_API_KEY=your-api-key
Or use a third-party provider (e.g. OpenRouter):
export ANTHROPIC_BASE_URL=https://openrouter.ai/api
export ANTHROPIC_API_KEY=your-openrouter-key
export ANTHROPIC_MODEL=anthropic/claude-sonnet-4-6
These can also be passed programmatically via options.env or apiKey/baseURL in createAgent().
Core API
query({ prompt, options }) — Streaming, compatible with official SDK
Returns an AsyncGenerator<SDKMessage>. Drop-in replacement for @anthropic-ai/claude-agent-sdk.
import { query } from '@shipany/open-agent-sdk'
for await (const message of query({
prompt: 'Find and fix the bug in auth.ts',
options: {
allowedTools: ['Read', 'Edit', 'Bash'],
permissionMode: 'acceptEdits',
},
})) {
if (message.type === 'assistant' && message.message?.content) {
for (const block of message.message.content) {
if ('text' in block) process.stdout.write(block.text)
else if ('name' in block) console.log(`\n[Tool used: ${block.name}]`)
}
} else if (message.type === 'result') {
console.log(`\nDone: ${message.subtype}`)
}
}
createAgent(options) — Reusable agent with session state
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({
model: 'claude-sonnet-4-6',
systemPrompt: 'You are a senior TypeScript engineer. Be concise.',
maxTurns: 20,
})
// Blocking call
const result = await agent.prompt('Read package.json and describe the project')
console.log(result.text)
console.log(`Tokens used: ${result.usage.input_tokens + result.usage.output_tokens}`)
// Streaming call
for await (const msg of agent.query('Now add JSDoc to all exported functions')) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if ('text' in block) process.stdout.write(block.text)
}
}
}
// Session management
const history = agent.getMessages() // full conversation history
agent.clear() // reset session
Options Reference
| Option | Type | Default | Description |
|---|---|---|---|
model |
string |
claude-sonnet-4-6 |
Claude model ID |
apiKey |
string |
ANTHROPIC_API_KEY env |
API key |
baseURL |
string |
Anthropic API | Override for third-party providers |
cwd |
string |
process.cwd() |
Working directory for file/shell tools |
systemPrompt |
string |
— | Custom system prompt prepended to agent |
tools |
Tool[] |
All built-in | Override the full tool list |
allowedTools |
string[] |
all | Whitelist specific tools by name |
permissionMode |
string |
bypassPermissions |
acceptEdits, bypassPermissions, plan, default |
maxTurns |
number |
100 |
Maximum agentic loop iterations |
maxBudgetUsd |
number |
— | Spend cap in USD |
mcpServers |
object |
— | MCP server configs (stdio/SSE/HTTP) |
agents |
object |
— | Named subagent definitions |
hooks |
object |
— | Lifecycle hooks: PreToolUse, PostToolUse, Stop |
thinking |
object |
— | Extended thinking config |
env |
object |
— | Environment variables passed to tools |
resume |
string |
— | Resume prior session by session ID |
canUseTool |
function |
— | Custom permission callback (tool, input) => boolean |
includePartialMessages |
boolean |
false |
Emit raw streaming events |
Common Patterns
Multi-turn conversation with context
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({ model: 'claude-sonnet-4-6' })
const r1 = await agent.prompt('Read src/index.ts and explain the architecture')
console.log(r1.text)
// Context from r1 is preserved automatically
const r2 = await agent.prompt('Refactor the error handling to use a Result type')
console.log(r2.text)
Restrict to read-only tools
import { query } from '@shipany/open-agent-sdk'
for await (const message of query({
prompt: 'Review this codebase for security issues',
options: {
allowedTools: ['Read', 'Glob', 'Grep'],
// No Write, Edit, or Bash — agent cannot modify files
},
})) {
if (message.type === 'result') console.log('Review complete')
}
Custom tools
import { createAgent, getAllBaseTools } from '@shipany/open-agent-sdk'
const dbQueryTool = {
name: 'QueryDatabase',
description: 'Run a read-only SQL query and return results as JSON',
inputJSONSchema: {
type: 'object',
properties: {
sql: { type: 'string', description: 'The SQL query to run' },
},
required: ['sql'],
},
get inputSchema() {
return { safeParse: (v: unknown) => ({ success: true, data: v }) }
},
async prompt() { return this.description },
async call(input: { sql: string }) {
// Replace with your actual DB client
const rows = [{ id: 1, name: 'Example' }]
return { data: JSON.stringify(rows) }
},
userFacingName: () => 'QueryDatabase',
isReadOnly: () => true,
isConcurrencySafe: () => true,
mapToolResultToToolResultBlockParam: (data: string, id: string) => ({
type: 'tool_result' as const,
tool_use_id: id,
content: data,
}),
}
const agent = createAgent({
tools: [...getAllBaseTools(), dbQueryTool],
})
const result = await agent.prompt('How many users signed up in the last 7 days?')
console.log(result.text)
MCP server integration
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({
mcpServers: {
filesystem: {
command: 'npx',
args: ['-y', '@modelcontextprotocol/server-filesystem', '/tmp'],
},
playwright: {
command: 'npx',
args: ['@playwright/mcp@latest'],
},
},
})
const result = await agent.prompt('List all .json files in /tmp')
console.log(result.text)
Subagents for parallel / delegated work
import { query } from '@shipany/open-agent-sdk'
for await (const message of query({
prompt: 'Use the security-auditor agent to audit src/ for vulnerabilities',
options: {
allowedTools: ['Read', 'Glob', 'Grep', 'Agent'],
agents: {
'security-auditor': {
description: 'Expert security auditor for TypeScript codebases.',
prompt: 'Identify OWASP Top 10 vulnerabilities and suggest fixes.',
tools: ['Read', 'Glob', 'Grep'],
},
},
},
})) {
if (message.type === 'assistant' && message.message?.content) {
for (const block of message.message.content) {
if ('text' in block) console.log(block.text)
}
}
}
Custom permission callback
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({
canUseTool: (toolName: string, input: unknown) => {
// Prevent deletion commands
if (toolName === 'Bash') {
const cmd = (input as { command?: string }).command ?? ''
if (cmd.includes('rm ') || cmd.includes('drop table')) return false
}
return true
},
})
Lifecycle hooks
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({
hooks: {
PreToolUse: async ({ tool, input }) => {
console.log(`About to run tool: ${tool} with input:`, input)
},
PostToolUse: async ({ tool, output }) => {
console.log(`Tool ${tool} finished`)
},
Stop: async ({ result }) => {
console.log('Agent stopped. Final result:', result)
},
},
})
Resume a previous session
import { createAgent } from '@shipany/open-agent-sdk'
// First session
const agent1 = createAgent({ model: 'claude-sonnet-4-6' })
const r1 = await agent1.prompt('Read ARCHITECTURE.md')
const sessionId = r1.sessionId // save this
// Later — resume where you left off
const agent2 = createAgent({
model: 'claude-sonnet-4-6',
resume: sessionId,
})
const r2 = await agent2.prompt('Now implement the TODO in section 3')
Built-in Tools Reference
| Tool | Read-only | Description |
|---|---|---|
Read |
✅ | Read files, images, PDFs with line numbers |
Glob |
✅ | Find files by glob pattern |
Grep |
✅ | Search file contents with regex (uses ripgrep) |
WebFetch |
✅ | Fetch and parse web pages |
WebSearch |
✅ | Web search |
Write |
❌ | Create or overwrite files |
Edit |
❌ | Precise string replacement in files |
Bash |
❌ | Execute shell commands |
Agent |
— | Spawn subagents |
TodoWrite |
❌ | Manage todo lists |
NotebookEdit |
❌ | Edit Jupyter notebooks |
TaskCreate/Update/List |
— | Task management |
TeamCreate/Delete |
— | Agent team management |
EnterPlanMode/ExitPlanMode |
— | Plan approval workflow |
EnterWorktree/ExitWorktree |
— | Git worktree isolation |
ListMcpResources/ReadMcpResource |
✅ | MCP resource access |
Architecture: How It Differs from Official SDK
Official @anthropic-ai/claude-agent-sdk:
Your code → SDK → spawn cli.js subprocess → stdin/stdout JSON → Anthropic API
Open Agent SDK:
Your code → SDK → QueryEngine (in-process) → Anthropic API (direct HTTP)
This means:
- No CLI installation required in the deployment environment
- Works in serverless (AWS Lambda, Vercel, Cloudflare Workers with Node.js compat)
- Works in Docker with just
npm install - Works in CI/CD without CLI setup steps
- Programmatic access to the full agent engine
Troubleshooting
Error: ANTHROPIC_API_KEY is not set
→ Export the env var or pass apiKey directly in createAgent({ apiKey: process.env.MY_KEY }).
Agent exceeds maxTurns without completing
→ Increase maxTurns or narrow the task. Check message.subtype === 'max_turns' in the result.
Tool not found / allowedTools not working
→ Tool names are case-sensitive: 'Read', 'Edit', 'Bash', 'Glob', 'Grep', 'WebFetch', etc.
Using with OpenRouter or other providers
→ Set ANTHROPIC_BASE_URL to the provider's base URL and use their model string format, e.g. anthropic/claude-sonnet-4-6 for OpenRouter.
Agent modifies files unexpectedly
→ Use allowedTools: ['Read', 'Glob', 'Grep'] to restrict to read-only tools, or set permissionMode: 'plan' to require approval before edits.
MCP server fails to start
→ Ensure the MCP server package is installed or accessible via npx. Check command and args match what the MCP package expects.
TypeScript types missing
→ The package ships its own types. Ensure "moduleResolution": "bundler" or "node16" in tsconfig.json and "esModuleInterop": true.
Quick Reference
// Minimal one-shot agent
import { createAgent } from '@shipany/open-agent-sdk'
const agent = createAgent({ model: 'claude-sonnet-4-6' })
const { text } = await agent.prompt('Summarize README.md in 3 bullet points')
console.log(text)