Browserbase MCP server for AI agents

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API KEY

CLOUD BROWSERS

Developer Tools

Browserbase gives your agent cloud browsers: start and release sessions, fetch pages and search the web, run browser agents on natural-language tasks, invoke deployed Functions, and read session logs, replays, downloads, and project usage.

  • Per-user credentials: each call uses the actual user's API key, never a shared bot.
  • Encrypted per-tenant vault: AES-256, resolved at request time, never in LLM context.
  • Scoped before every call: pre-call scope check, 90-day SIEM-exportable audit chain.
Browserbase
agent · Acme Q3
Run
Did last night's pricing scrape session finish cleanly?
S
browserbase_get_session
113ms
Browser agent
The session completed in 6 minutes and downloaded 3 files. It used about 7 browser minutes with no errors.
Sources: 1 session, 3 downloads
browserbase
1 session
18:29
Message Claude...

Tools your browser agent reaches for on Browserbase, scoped per user.

CALL ANY TOOL
38 tools for cloud browsers in Browserbase: start and release sessions, fetch pages and search the web, create and run browser agents, invoke Functions, save contexts, and read session logs, replays, recordings, downloads, and usage.
browserbase_create_agent
Create agent
Create a reusable Browserbase custom agent with a name, a system prompt and a result schema. Returns the new agent's agentId, name, systemPrompt, resultSchema, createdAt and updatedAt. Use this to save instructions you run often, then pass the agentId to browserbase_run_agent. Use browserbase_update_agent to change an existing agent.
Parameters
Name
Type
Required
Description
name
string
Required
Name for the agent, 1 to 255 characters, shown in the dashboard and API responses. Example: Pricing checker
result_schema
object
Optional
JSON Schema that runs of this agent should return their result in. Runs can override it. Example: {"type": "object", "properties": {"price": {"type": "number"}}}
system_prompt
string
Optional
Instructions that steer the agent on every run that uses it. Example: You check competitor pricing pages and report prices in USD.
browserbase_create_context
Create context
browserbase_create_session
Create session
browserbase_delete_agent
Delete agent
browserbase_delete_context
Delete context
browserbase_delete_download
Download delete
browserbase_fetch_page
Fetch page
browserbase_get_agent
Get agent
browserbase_get_agent_run
Run get agent
browserbase_get_context
Get context
browserbase_get_download
Download get
browserbase_get_function
Get function
browserbase_get_function_invocation
Get function invocation
browserbase_get_function_invocation_logs
Get function invocation logs
browserbase_get_project
Get project
browserbase_get_session
Get session
browserbase_get_session_live_urls
Get session live urls
browserbase_get_session_logs
Get session logs
browserbase_invoke_function
Invoke function
browserbase_list_agent_run_messages
List agent run messages
browserbase_list_agent_runs
List agent runs
browserbase_list_agents
List agents
browserbase_list_projects
List projects
browserbase_list_session_downloads
List session downloads
browserbase_list_session_recording_downloads
List session recording downloads
browserbase_release_session
Release session
browserbase_resume_agent_run
Run resume agent
browserbase_run_agent
Run agent
browserbase_search_web
Search web
browserbase_update_agent
Update agent

For more tools, view docs.

Build your Agent
Same auth pattern across LangChain, OpenAI, Anthropic, and Google ADK.
Python · LlamaIndex
import { ScalekitClient } from "@scalekit-sdk/node";
import { createReactAgent } from "@langchain/langgraph/prebuilt";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

// Browserbase tools scoped to this user
const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["browserbase"], toolNames: [
    "browserbase_run_agent",
    "browserbase_get_agent_run",
    "browserbase_list_agent_run_messages"] },
  pageSize: 100,
});

const agent = createReactAgent({ llm, tools });
await agent.invoke({ messages: [{ role: "user", content: "Find the pricing tiers on globex.com and summarize them" }] });
import OpenAI from "openai";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const openai = new OpenAI();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["browserbase"] }, pageSize: 100,
});

const res = await openai.chat.completions.create({
  model: "gpt-5",
  messages: [{ role: "user", content: "Find the pricing tiers on globex.com and summarize them" }],
  tools,
});

// Execute the tool call with the user's vaulted Browserbase API key
await sk.tools.executeTool(res.choices[0].message.tool_calls[0], "user_123");
import Anthropic from "@anthropic-ai/sdk";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);
const anthropic = new Anthropic();

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["browserbase"] }, pageSize: 100,
});

const msg = await anthropic.messages.create({
  model: "claude-sonnet-5",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Find the pricing tiers on globex.com and summarize them" }],
  tools,
});

// Tool call runs with the user's vaulted Browserbase API key
await sk.tools.executeTool(msg.content, "user_123");
import { Agent } from "@google/adk/agents";
import { ScalekitClient } from "@scalekit-sdk/node";

const sk = new ScalekitClient(env.SCALEKIT_ENV_URL, env.SCALEKIT_CLIENT_ID, env.SCALEKIT_CLIENT_SECRET);

const { tools } = await sk.tools.listScopedTools("user_123", {
  filter: { connectionNames: ["browserbase"] }, pageSize: 100,
});

const agent = new Agent({
  name: "browser_agent",
  model: "gemini-2.5-pro",
  instruction: "Browserbase tools scoped to this user",
  tools,
});

await agent.run("Find the pricing tiers on globex.com and summarize them");
Try these prompts
Copy any prompt into your agent. Each maps directly to a Browserbase tool. Click to copy, paste into your agent, done.
Sessions
Copy the prompt
Copied
Start a Browserbase session with my saved Acme login context.
Copy the prompt
Copied
Get the live view URL for the running session.
Copy the prompt
Copied
Release session abc123 now.
Agents and pages
Copy the prompt
Copied
Run a browser agent to find the pricing tiers on globex.com.
Copy the prompt
Copied
Fetch https://acme.com/pricing as markdown.
Copy the prompt
Copied
Search the web for recent posts about Browserbase Functions.
Debugging and usage
Copy the prompt
Copied
Show the replay of last night's failed session.
Copy the prompt
Copied
List the files that session downloaded.
Copy the prompt
Copied
How many browser minutes has our project used so far?
SEE HOW AUTH WORKS
Each user connects their own Browserbase API key once, and Scalekit sends it with every call. API keys stay vaulted, every call is scope checked, and every action is logged.
1
Authorize
Your user connects
Browserbase
once. We tie it to their identity and the meetings they approved — no shared bot account, no org-wide access
Who:
user ‘A’
when:
Once per user
access:
Limited to user
2
Store
Their
Browserbase
token lives in a vault scoped to them. User A's meetings are never reachable by an agent acting for user B, even on the same connection
vault:
encrypted
scope:
per-user
tokens:
auto-refreshed
3
Resolve
When your agent calls a
Browserbase
tool, we fetch the right token server-side. It never touches your agent, never appears in the LLM context, never shows up in your logs
speed:
~40ms
check:
before every call
seen by:
nobody
4
Audit
Every
Browserbase
tool call is logged — who triggered it, which meeting was fetched, what came back. 90 days of history, tied to the user who authorized it
history:
90 days
export:
SIEM-ready
logged:
every call
Test other agents
See the same per-user auth pattern across other developer and automation connectors.
GTM and RevOps Teams
Competitive intelligence briefing agent
Scans Gong calls for competitor mentions, matches each one to its Notion battlecard, and DMs every affected rep a single Slack digest per cycle. Every call runs as the PMM who owns the briefing, never a shared bot.
Engineering Teams
DevOps assistant agent
Polls GitHub for failing checks and stale PRs, opens Linear issues for the ones that need work, and posts a daily digest to Slack. It acts as the engineer, not a shared service account.
Test other agents
See the same per-user auth pattern across other developer and automation connectors.
GTM
Competitive intelligence briefing agent
Scan Gong calls for competitor mentions, match each one to its Notion battlecard, and DM every affected rep a single Slack digest.
ENGINEERING
DevOps assistant agent
Poll GitHub for failing checks and stale pull requests, open Linear issues for the ones that need work, and digest to Slack.
Why Scalekit
Secure your agent's access. Connectors ship in minutes
01.
Shared tokens break per-user analytics
A shared Browserbase API key looks fine in a demo. In production every session and agent run looks like one service account, and you cannot tell which user triggered it. Scalekit resolves the credential of the actual user who triggered the agent, never a shared bot.
// shared key
audit → bot_service_account

// scalekit
audit → user_abc ✓
02.
Authentication is not authorization
03.
Multi-tenancy is architectural
04.
Browserbase today. Ten connectors tomorrow.
“Our agents act across Salesforce, Gong, Google Drive, and more, on behalf of every customer. Scalekit behind the scenes meant we can keep adding tools without ever rebuilding how credentials or tool calling work.”
Venu Madhav Kattagoni
Head of Engineering / Von
FAQs
Frequently Asked Questions
Does the agent access Browserbase as the user or through a shared API key?
As the user. Each user connects their own Browserbase API key once, and Scalekit sends it with every call. Audit logs attribute every session, agent run, and Function invocation to that user, not a shared service account.
Where is the Browserbase API key stored?
In Scalekit's managed AES-256 token vault, namespaced per tenant. To rotate it, the user reconnects with a new API key. Revocation is a single dashboard action. Credentials never appear in prompts, logs, or LLM context.
Can I limit what the agent does in Browserbase?
Yes. Filter by tool name in listScopedTools to expose only what you want, for example the session and replay read tools without browserbase_delete_context, which permanently deletes the cookies, storage, and logins saved in a context. Scalekit also enforces scope checks before every API call.
What happens when a user revokes Browserbase access?
The connection is invalidated on the next tool call. Subsequent requests for that user fail closed with a clear error. Other users in the tenant remain unaffected. The event is logged for audit.
Can the agent run a browser task without driving the browser step by step?
Yes. browserbase_run_agent starts a Browserbase browser agent that completes a natural-language task, browserbase_get_agent_run tracks its status, and browserbase_list_agent_run_messages returns what it did. For a single page, browserbase_fetch_page fetches a URL without starting a browser.
Start in your coding agent
Up and running in one command
Install the Scalekit skill in your editor of choice. Connector, auth, tools, prompt, all wired up
Claude Code REPL
/plugin marketplace add scalekit-inc/claude-code-authstack
/plugin install agentkit@scalekit-auth-stack
Cursor Code REPL
# ~/.cursor/mcp.json
{
""mcpServers"": {
""browserbase"": {
""url"": ""https://mcp.scalekit.com/browserbase"",
""headers"": { ""Authorization"": ""Bearer $SCALEKIT_TOKEN"" }
}
}
}
Codex Code REPL
# ~/.codex/config.toml
[mcp_servers.browserbase]
url = ""https://mcp.scalekit.com/browserbase""
auth_env = ""SCALEKIT_TOKEN""
Copilot Code REPL
# .vscode/mcp.json
{
""servers"": {
""browserbase"": {
""url"": ""https://mcp.scalekit.com/browserbase"",
""type"": ""http""
}
}
}