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@ai-sdk/mcp
Advanced tools
The Model Context Protocol (MCP) client for the
AI SDK lets you connect to MCP servers and use their
tools with AI SDK functions like generateText and streamText.
The MCP client is available in the @ai-sdk/mcp module. You can install it with
npm i @ai-sdk/mcp ai zod
If you use coding agents such as Claude Code or Cursor, we highly recommend adding the AI SDK skill to your repository:
npx skills add vercel/ai
Create an MCP client with createMCPClient(), fetch the server tools with
mcpClient.tools(), and pass them to an AI SDK call:
import { createMCPClient } from '@ai-sdk/mcp';
import { generateText, isStepCount } from 'ai';
const mcpClient = await createMCPClient({
transport: {
type: 'http',
url: 'https://your-server.com/mcp',
headers: {
Authorization: `Bearer ${process.env.MCP_API_KEY}`,
},
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: 'openai/gpt-6-astra',
tools,
stopWhen: isStepCount(10),
prompt: 'Use the available tools to answer the user question.',
});
console.log(text);
} finally {
await mcpClient.close();
}
The client converts MCP tool definitions into AI SDK tools, so model calls can
use them through the standard tools option.
Use list, subscribe, refresh, and unsubscribe through
client.experimental_events on the same createMCPClient instance. Configure
experimental_events: { store } with private durable storage shared with
experimental_createMCPEventWebhook, which you mount at your callback URL.
Subscription creation persists delivery.url and the generated signing secret
before contacting the server, enabling signed callback verification during the
subscribe request. The receiver verifies raw request bytes and checks event
envelopes before invoking your handler. Optional callbacks let your application
validate filters and event data. Agent execution and durable deduplication
remain application concerns; closing the client does not unsubscribe.
See the MCP Events guide and the local server/client example.
The client supports legacy MCP protocol versions through the initialize
handshake and MCP 2026-07-28 through stateless protocol discovery. The
built-in stdio transport probes with server/discover and falls back to the
legacy handshake when connected to an older server.
Custom transports can opt into the same negotiation by setting
supportsProtocolVersionDiscovery to true. Modern requests include the
protocol version, client capabilities, and client information in _meta.
For streaming responses, close the MCP client when the stream finishes:
import { createMCPClient } from '@ai-sdk/mcp';
import { streamText } from 'ai';
const mcpClient = await createMCPClient({
transport: {
type: 'http',
url: 'https://your-server.com/mcp',
},
});
const result = streamText({
model: 'openai/gpt-6-astra',
tools: await mcpClient.tools(),
prompt: 'Use the available tools to answer the user question.',
onEnd: async () => {
await mcpClient.close();
},
});
for await (const textPart of result.textStream) {
process.stdout.write(textPart);
}
HTTP is recommended for production deployments:
Session persistence applies only to legacy MCP protocol versions. MCP
2026-07-28 is stateless and does not use session ids or cached initialize
results.
import { createMCPClient } from '@ai-sdk/mcp';
const savedSession = await loadMcpSession();
let currentSessionId = savedSession?.sessionId;
const mcpClient = await createMCPClient({
transport: {
type: 'http',
url: 'https://your-server.com/mcp',
initialSessionId: savedSession?.sessionId,
initialProtocolVersion: savedSession?.initializeResult.protocolVersion,
terminateSessionOnClose: false,
onSessionIdChange: sessionId => {
currentSessionId = sessionId;
},
onSessionExpired: sessionId => {
if (currentSessionId === sessionId) {
currentSessionId = undefined;
void clearMcpSession();
}
},
},
initialInitializeResult: savedSession?.initializeResult,
});
if (currentSessionId) {
await saveMcpSession({
sessionId: currentSessionId,
initializeResult: mcpClient.initializeResult,
});
}
SSE is also supported for MCP servers that use Server-Sent Events:
const mcpClient = await createMCPClient({
transport: {
type: 'sse',
url: 'https://your-server.com/sse',
},
});
For local MCP servers, you can use stdio transport from the @ai-sdk/mcp/mcp-stdio
subpath:
import { createMCPClient } from '@ai-sdk/mcp';
import { Experimental_StdioMCPTransport } from '@ai-sdk/mcp/mcp-stdio';
const mcpClient = await createMCPClient({
transport: new Experimental_StdioMCPTransport({
command: 'node',
args: ['server.js'],
}),
});
Please check out the AI SDK MCP documentation for more information.
Managed backends can implement Experimental_MCPEventAdapter and configure
experimental_events: { adapter } instead of a store. Its createAdapter()
method receives { transport } metadata (HTTP/SSE type and URL, or
{ type: 'custom' } for custom transports) and returns Experimental_MCPEventOperations
bound to the authorized account. Catalog discovery still
uses the authenticated MCP transport; subscribe/get/list/unsubscribe delegate
to the backend, which owns renewal and webhook delivery. Managed clients do not
expose refresh(). See the managed subscription reference.
FAQs
Unknown package
The npm package @ai-sdk/mcp receives a total of 1,298,295 weekly downloads. As such, @ai-sdk/mcp popularity was classified as popular.
We found that @ai-sdk/mcp demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.

Product
Socket Threat Intel now shows which malware campaigns were blocked or detected in your organization, with links to scans and Firewall events.

Security News
Fixes for eMudhra and Brotli are out. Getting them everywhere they’re needed means tracking down bundled libraries, runtimes, and certificate stores.

Threat Research
/Security News
Socket uncovered secret-stealing workflows that ran in LiteLLM’s GitHub repository 11 days before the supply chain attack on PyPI and Docker.