Build scalable AI agents with optimized authentication workflows using Model Context Protocol.
Authentication is a hidden bottleneck in AI agent efficiency. When AI agents need to access user data, perform actions on behalf of users, or integrate with authenticated APIs, traditional authentication patterns can consume thousands of tokens, expose sensitive credentials, and create security vulnerabilities. The Model Context Protocol (MCP) combined with code execution transforms this landscape, enabling agents to authenticate efficiently while maintaining security and privacy.
@warpy-auth-sdk/core implements MCP with a code-execution-first approach, allowing AI agents to authenticate users with scoped, time-limited access while minimizing context window usage and protecting sensitive data. This guide explores how code execution with MCP creates more efficient, secure, and scalable AI agent authentication.
Traditional authentication patterns designed for human users create significant challenges when applied to AI agents:
Agents often need to repeatedly pass authentication credentials and tokens through their context window. When using direct tool calls, every authentication attempt includes:
Impact: A single authentication workflow with 5 providers can consume 10,000+ tokens just for provider definitions and responses, leaving less room for actual task logic.
Multi-step authentication flows compound the problem:
Token-heavy authentication workflow
// Step 1: Agent calls tool to list available providers (800 tokens)
const providers = await listAuthProviders(); // Returns full config for 10+ providers
// Step 2: Agent selects provider and initiates auth (1,200 tokens)
const authUrl = await getAuthUrl({
provider: 'google',
scopes: ['email', 'profile'],
redirectUri: 'https://example.com/callback'
});
// Step 3: After OAuth callback, agent exchanges code (2,500 tokens)
const result = await exchangeAuthCode({
provider: 'google',
code: 'abc123',
state: 'xyz789'
}); // Returns full user profile + token + refresh token + provider metadata
// Step 4: Agent uses token to fetch additional data (1,500 tokens)
const userData = await fetchUserData({
token: result.accessToken
}); // Returns complete user object with all fields
// Total: ~6,000+ tokens consumed, sensitive data exposed in contextSupporting multiple authentication providers creates exponential complexity:
This complexity fragments agent decision-making and increases the risk of authentication errors or security misconfigurations.
Passing full credentials and tokens through the agent's context creates risks:
Code execution transforms MCP authentication from a series of tool calls into a programmatic API that agents can use efficiently. Instead of passing provider configurations and credentials through the context window, agents write code that interacts with authentication endpoints locally, keeping sensitive data isolated and reducing token consumption by up to 95%.
With code execution, MCP tools are presented to agents as a virtual filesystem of TypeScript/JavaScript modules that can be imported and used programmatically:
Tools presented as importable modules
// Virtual filesystem structure visible to agents
servers/
├── warpy-auth/
│ ├── agentLogin.ts // Creates short-lived agent tokens
│ ├── getSession.ts // Verifies tokens and retrieves session info
│ ├── revokeToken.ts // Invalidates tokens immediately
│ └── types.ts // Shared type definitions
// Agent code can import and use these modules directly
import * as auth from './servers/warpy-auth';
// Efficient, isolated authentication
const { token } = await auth.agentLogin({
userId: 'user-123',
scopes: ['debug', 'read'],
expiresIn: '15m'
});
// Token stays in execution environment, never passed to model
const profile = await fetchWithAuth(token);
console.log('Authentication successful'); // Only confirmation goes to modelCode execution enables progressive disclosure—agents only load the authentication capabilities they actually need, when they need them:
Load provider schemas only when needed
// Traditional: All providers loaded upfront (10,000+ tokens)
const allProviders = await listProviders(); // Full config for 10+ providers
// Code Execution: Load providers on-demand (500 tokens)
import { searchAuthTools } from './servers/warpy-auth';
// Agent only discovers tools it needs
if (taskRequiresGoogleAuth) {
const googleTools = await searchAuthTools({ provider: 'google' });
// Only Google-specific functions loaded
}When agents execute authentication code, sensitive data can be automatically masked before being returned to the model:
Automatic credential masking
import * as auth from './servers/warpy-auth';
// Agent code runs in isolated environment
const { token } = await auth.agentLogin({
userId: 'user-123',
scopes: ['debug', 'read']
});
// Fetch user profile with token (token never leaves execution env)
const profile = await fetch('/api/user/profile', {
headers: { 'Authorization': `Bearer ${token}` }
}).then(res => res.json());
// Automatic masking applied before returning to model
console.log(`Profile loaded for ${profile.email}`);
// Model sees: "Profile loaded for [EMAIL_1]"
// Real data available in execution environment for API calls
// Masked references available in model context for trackingHere's how the authentication flow differs between traditional MCP and code execution:
Traditional vs Code Execution
```mermaid
graph TD
subgraph Traditional MCP
A1[Agent Context] -->|Full provider configs| B1[Tool: agent_login]
B1 -->|Full token + user data| A1
A1 -->|Token in context| C1[Tool: get_session]
C1 -->|Complete profile| A1
A1 -->|All data visible| D1[Task Execution]
end
subgraph Code Execution with MCP
A2[Agent Context] -->|Import statement only| B2[Execution Env]
B2 -->|agentLogin function| C2[Auth Logic]
C2 -->|Token stays local| B2
B2 -->|Masked result only| A2
B2 -->|Direct API calls| D2[Task Execution]
end
```
**Token Usage:**
- Traditional: ~6,000 tokens per auth flow
- Code Execution: ~300 tokens per auth flow (95% reduction)By keeping authentication logic in code rather than tool calls, agents can perform complex authentication workflows with minimal token usage:
Code execution creates a natural privacy boundary between authentication credentials and the model:
Keep sensitive data out of model context
import * as auth from './servers/warpy-auth';
import { maskPII } from './servers/warpy-auth/privacy';
// Authenticate and fetch user data
const { token } = await auth.agentLogin({
userId: 'user-123',
scopes: ['read:profile', 'read:orders']
});
const user = await fetchUserProfile(token);
const orders = await fetchUserOrders(token);
// Mask PII automatically before logging
const maskedUser = maskPII(user, {
email: '[EMAIL_1]',
phone: '[PHONE_1]',
address: '[ADDRESS_1]'
});
console.log(`Loaded profile for ${maskedUser.email}`);
console.log(`Found ${orders.length} orders`);
// Model Context Sees:
// "Loaded profile for [EMAIL_1]"
// "Found 5 orders"
// Execution Environment Has:
// Full access to real email, phone, address for API operations
// Can make authenticated API calls with real data
// Model never sees unmasked PIIThis pattern ensures compliance with privacy regulations (GDPR, CCPA) while still allowing agents to perform useful work with user data.
Code execution allows agents to implement sophisticated authentication patterns:
Save and reuse tokens across agent sessions
import * as auth from './servers/warpy-auth';
import { readFile, writeFile } from 'fs/promises';
// Check for existing session
let sessionData;
try {
const cached = await readFile('./workspace/.auth-session', 'utf-8');
sessionData = JSON.parse(cached);
// Verify token is still valid
const verification = await auth.getSession({ token: sessionData.token });
if (!verification.success) {
throw new Error('Session expired');
}
} catch {
// No valid session, create new one
const result = await auth.agentLogin({
userId: 'user-123',
scopes: ['debug', 'read'],
expiresIn: '1h'
});
sessionData = {
token: result.token,
expires: result.expires,
userId: 'user-123'
};
// Persist for future tasks
await writeFile(
'./workspace/.auth-session',
JSON.stringify(sessionData),
'utf-8'
);
}
console.log('Authenticated session ready');
// Agent can now perform multiple operations without re-authenticatingCode execution enables security patterns that are difficult or impossible with direct tool calls:
Track auth operations without context pollution
import * as auth from './servers/warpy-auth';
import { appendFile } from 'fs/promises';
async function auditedLogin(userId: string, scopes: string[], reason: string) {
const timestamp = new Date().toISOString();
// Perform authentication
const result = await auth.agentLogin({
userId,
scopes,
agentId: 'production-agent',
expiresIn: '15m'
});
// Log to secure audit file (not visible to model)
await appendFile('./workspace/.audit-log', JSON.stringify({
timestamp,
action: 'agent_login',
userId,
scopes,
reason,
success: result.success,
tokenHash: hashToken(result.token) // Never log full token
}) + '\n');
console.log(`Authenticated for: ${reason}`);
return result;
}
// Model only sees high-level confirmation
// Full audit trail preserved in execution environmentAgents can discover authentication tools dynamically based on task requirements:
Load only needed authentication methods
import { searchAuthTools } from './servers/warpy-auth';
// Agent determines authentication needs based on task
const taskContext = analyzeTask(userRequest);
if (taskContext.requiresOAuth) {
// Load OAuth-specific tools
const oauthTools = await searchAuthTools({
type: 'oauth',
provider: taskContext.preferredProvider
});
// Only OAuth schemas loaded into context
}
if (taskContext.requires2FA) {
// Load 2FA tools separately
const twoFATools = await searchAuthTools({ type: '2fa' });
// 2FA schemas loaded only when needed
}
// Result: 80% reduction in unnecessary schema loadingTraditional MCP authentication without code execution:
Simple but inefficient
// Agent makes direct tool call
const response = await fetch('/api/mcp', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
tool: 'agent_login',
args: {
userId: 'user-123',
scopes: ['debug', 'read'],
agentId: 'claude-assistant',
expiresIn: '15m'
}
})
});
const result = await response.json();
// Full response visible in agent context
// Token: "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9..."
// Expires: "2024-11-06T15:30:00Z"
// Message: "Agent claude-assistant logged in..."
// Use token for authenticated requests
const userData = await fetch('/api/user/profile', {
headers: { 'Authorization': `Bearer ${result.token}` }
});
const profile = await userData.json();
// Full user profile in context
// { email: "user@example.com", name: "John Doe", ... }
// Token Usage: ~1,500 tokens for auth + responseUsing code execution for efficient, secure authentication:
Filesystem API structure
// File: servers/warpy-auth/agentLogin.ts
import { callMCPTool } from '../../../client.js';
export interface AgentLoginInput {
userId: string;
scopes: string[];
agentId?: string;
expiresIn?: string;
}
export interface AgentLoginResponse {
success: boolean;
token?: string;
expires?: string;
error?: string;
}
export async function agentLogin(
input: AgentLoginInput
): Promise<AgentLoginResponse> {
return callMCPTool<AgentLoginResponse>('warpy_auth__agent_login', {
userId: input.userId,
scopes: input.scopes,
agentId: input.agentId || 'default-agent',
expiresIn: input.expiresIn || '15m'
});
}
// File: servers/warpy-auth/getSession.ts
export interface GetSessionInput {
token: string;
}
export interface SessionInfo {
userId: string;
email?: string;
scopes: string[];
agentId?: string;
}
export async function getSession(
input: GetSessionInput
): Promise<{ success: boolean; session?: SessionInfo; error?: string }> {
return callMCPTool('warpy_auth__get_session', input);
}
// File: servers/warpy-auth/revokeToken.ts
export async function revokeToken(
token: string
): Promise<{ success: boolean; error?: string }> {
return callMCPTool('warpy_auth__revoke_token', { token });
}Agent code using the filesystem API:
Efficient auth workflow with code execution
import * as auth from './servers/warpy-auth';
// Authenticate (token stays in execution environment)
const { success, token, error } = await auth.agentLogin({
userId: 'user-123',
scopes: ['debug', 'read'],
expiresIn: '15m'
});
if (!success) {
console.log(`Auth failed: ${error}`);
throw new Error('Authentication failed');
}
console.log('Authentication successful');
// Model sees: "Authentication successful" (8 tokens)
// Token never enters model context
// Use token for API calls
const profile = await fetch('/api/user/profile', {
headers: { 'Authorization': `Bearer ${token}` }
}).then(res => res.json());
// Mask sensitive data before logging
console.log(`Loaded profile for ${profile.email ? '[EMAIL]' : 'unknown'}`);
// Model sees: "Loaded profile for [EMAIL]" (7 tokens)
// Total token usage: ~50 tokens (vs 1,500 tokens traditional approach)
// 97% reduction in authentication token consumptionHandling complex authentication scenarios efficiently:
Long-running tasks with automatic token refresh
import * as auth from './servers/warpy-auth';
class AuthenticatedSession {
private token: string | null = null;
private expiresAt: Date | null = null;
private userId: string;
private scopes: string[];
constructor(userId: string, scopes: string[]) {
this.userId = userId;
this.scopes = scopes;
}
async ensureValid(): Promise<string> {
// Check if token exists and hasn't expired
if (this.token && this.expiresAt && this.expiresAt > new Date()) {
return this.token;
}
// Token expired or doesn't exist, refresh
console.log('Refreshing authentication...');
const result = await auth.agentLogin({
userId: this.userId,
scopes: this.scopes,
expiresIn: '15m'
});
if (!result.success || !result.token) {
throw new Error('Failed to refresh token');
}
this.token = result.token;
this.expiresAt = new Date(result.expires!);
console.log('Token refreshed successfully');
return this.token;
}
async authenticatedFetch(url: string, options: RequestInit = {}) {
const token = await this.ensureValid();
return fetch(url, {
...options,
headers: {
...options.headers,
'Authorization': `Bearer ${token}`
}
});
}
}
// Usage in long-running task
const session = new AuthenticatedSession('user-123', ['debug', 'read']);
// Agent performs multiple operations over time
for (let i = 0; i < 10; i++) {
// Token automatically refreshed if needed
const response = await session.authenticatedFetch('/api/data/batch/' + i);
const data = await response.json();
console.log(`Processed batch ${i + 1}/10`);
await sleep(120000); // 2 minute delay between batches
}
console.log('All batches processed successfully');
// Model Context: Only sees progress updates
// Token refresh happens transparently in execution environment
// No token exposure, no context bloat from refresh operationsImplementing comprehensive PII protection:
Automatic masking of sensitive data
import * as auth from './servers/warpy-auth';
// Privacy utility (runs in execution environment)
class PrivacyGuard {
private tokenMap = new Map<string, string>();
private counter = 0;
maskEmail(email: string): string {
if (!this.tokenMap.has(email)) {
this.tokenMap.set(email, `[EMAIL_${++this.counter}]`);
}
return this.tokenMap.get(email)!;
}
maskPhone(phone: string): string {
if (!this.tokenMap.has(phone)) {
this.tokenMap.set(phone, `[PHONE_${++this.counter}]`);
}
return this.tokenMap.get(phone)!;
}
maskObject<T extends Record<string, any>>(obj: T): T {
const masked = { ...obj };
if (masked.email) masked.email = this.maskEmail(masked.email);
if (masked.phone) masked.phone = this.maskPhone(masked.phone);
if (masked.address) masked.address = '[ADDRESS]';
if (masked.ssn) masked.ssn = '[SSN]';
return masked;
}
// Real data available for API calls
getRealValue(maskedValue: string): string | undefined {
for (const [real, masked] of this.tokenMap.entries()) {
if (masked === maskedValue) return real;
}
return undefined;
}
}
const privacy = new PrivacyGuard();
// Authenticate and fetch user data
const { token } = await auth.agentLogin({
userId: 'user-123',
scopes: ['read:profile', 'write:support_ticket']
});
const profile = await fetch('/api/user/profile', {
headers: { 'Authorization': `Bearer ${token}` }
}).then(res => res.json());
// Mask before any logging
const maskedProfile = privacy.maskObject(profile);
console.log(`User profile: ${JSON.stringify(maskedProfile)}`);
// Model sees: "{ email: '[EMAIL_1]', phone: '[PHONE_1]', name: 'John' }"
// Later, if agent needs to reference the email in API call:
// Use the mask for tracking, real value for API
console.log(`Creating support ticket for ${maskedProfile.email}`);
const realEmail = privacy.getRealValue(maskedProfile.email);
await createTicket({ email: realEmail, ... });
// Privacy preserved: Model only sees masks, APIs get real dataCode execution is ideal for:
Use direct MCP tool calls for:
Code execution requires proper sandboxing to prevent security issues:
Code execution with MCP transforms AI agent authentication from a context-heavy, security-risky operation into an efficient, privacy-preserving workflow. By presenting authentication as a programmatic API rather than a series of tool calls, agents can:
The @warpy-auth-sdk/core library makes code execution authentication accessible through its MCP implementation, with optional Warpy Cloud Shield for managed execution environments. Whether you're building debugging agents, automation systems, or AI-powered support tools, code execution with MCP provides the efficiency and security foundation for production-grade AI agents.
Continue learning about MCP authentication: