Bring Secrets Management
to Vercel AI SDK
Learn how to connect HashiCorp Vault to Vercel AI SDK and start using 50 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the HashiCorp Vault MCP Server?
Connect your HashiCorp Vault instance to any AI agent to automate secrets management and security operations through natural language.
What you can do
- Secrets Management — Read, write, and list KV secrets directly from your secure mounts using the KV engine.
- Dynamic Credentials — Generate on-demand credentials for Databases, AWS, and PKI certificates without manual intervention.
- Token Operations — Create, lookup, and renew tokens to manage session lifecycles and access control.
- Transit Encryption — Encrypt and decrypt data using Vault's transit engine to protect sensitive information without exposing keys.
- System Administration — Check cluster health, manage mounts, and configure auth methods or ACL policies directly.
How it works
- Subscribe to this server
- Provide your Vault Address and Token
- Start managing your infrastructure security from Claude, Cursor, or any MCP-compatible client
Who is this for?
- DevOps Engineers — automate secret rotation and infrastructure provisioning workflows.
- Security Teams — audit token accessors and manage ACL policies through conversation.
- Developers — fetch development secrets and generate local database credentials without leaving the IDE.
Built-in capabilities (50)
Login using AppRole authentication
Configure AWS root credentials
Configure a database connection
Configure Kubernetes authentication
Create or update an ACL policy
Create or update an AppRole role
Create an AWS role
Create a database role
Create a PKI role
Create a new Vault token
Create a new Transit key
Create a new Userpass user
Decrypt data using Transit engine
Delete the latest version of a KV v2 secret
Enable an audit device
Enable a new auth method
Enable a new secrets engine
Encrypt data using Transit engine
Generate a new Secret ID for an AppRole
Generate dynamic AWS credentials
Generate dynamic database credentials
Generate a new PKI root certificate
Check Vault initialization status
Generate OpenAPI V3 document of mounted backends
Check Vault system health
Login using GitHub personal access token
Initialize a new Vault cluster
Issue a new PKI certificate
Login using Kubernetes authentication
List ACL policies
List enabled audit devices
List enabled auth methods
List secrets in a KV v2 engine path
List mounted secrets engines
List token accessors (requires sudo)
Lookup a lease by ID
Lookup details about the current Vault token
Map a GitHub team to Vault policies
Read metadata for a KV v2 secret
Read a secret from KV v2 engine
Renew a lease
Renew the current Vault token
Revoke a lease
Revoke a PKI certificate
Revoke the current Vault token
Rotate a Transit key
Seal the Vault
Unseal the Vault with a key share
Login using Username and Password
Create or update a secret in KV v2 engine
Why Vercel AI SDK?
The Vercel AI SDK gives every HashiCorp Vault tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 50 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
- —
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
- —
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same HashiCorp Vault integration everywhere
- —
Built-in streaming UI primitives let you display HashiCorp Vault tool results progressively in React, Svelte, or Vue components
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Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
HashiCorp Vault in Vercel AI SDK
HashiCorp Vault and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect HashiCorp Vault to Vercel AI SDK through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for HashiCorp Vault in Vercel AI SDK
The HashiCorp Vault MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 50 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Vercel AI SDK only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
HashiCorp Vault for Vercel AI SDK
Every tool call from Vercel AI SDK to the HashiCorp Vault MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I check the remaining TTL and policies of my current session token?
Yes. Use the lookup_self_token tool. It returns the creation time, TTL, associated policies, and metadata for the token currently in use.
How do I retrieve a specific secret from a KV version 2 engine?
Use the read_kv_secret tool by providing the path to the secret. The agent will fetch the data and present the key-value pairs securely.
Is it possible to generate temporary database credentials through the agent?
Yes. If the database engine is configured, use generate_database_creds with the specific role name to receive a temporary username and password.
How does the Vercel AI SDK connect to MCP servers?
Import createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.
Can I use MCP tools in Edge Functions?
Yes. The AI SDK is fully edge-compatible. MCP connections work on Vercel Edge Functions, Cloudflare Workers, and similar runtimes.
Does it support streaming tool results?
Yes. The SDK provides streaming primitives like useChat and streamText that handle tool calls and display results progressively in the UI.
createMCPClient is not a function
Install: npm install @ai-sdk/mcp
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