Greptile MCP Server for Vercel AI SDKGive Vercel AI SDK instant access to 11 tools to Delete Repository, Get File Info, Get Greptile Usage, and more
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Greptile through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
Ask AI about this App Connector for Vercel AI SDK
The Greptile app connector for Vercel AI SDK is a standout in the Developer Tools category — giving your AI agent 11 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Greptile, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* 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
About Greptile MCP Server
Connect your Greptile account to any AI agent and unlock AI-powered codebase understanding through natural conversation.
The Vercel AI SDK gives every Greptile tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 11 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- AI Codebase Q&A — Ask natural language questions about one or more repositories and receive AI-generated answers with code references
- Contextual Follow-ups — Continue conversations with session context for multi-turn codebase exploration
- Semantic Code Search — Search across indexed repositories to find relevant files, functions, and code patterns
- File-Specific Search — Target searches within a specific file path for precise results
- Repository Indexing — Submit GitHub or GitLab repositories for indexing, check progress, and trigger re-indexing
- Repository Management — List all indexed repos, inspect file metadata, and remove outdated indexes
- Usage Monitoring — Track API consumption and rate limits
The Greptile MCP Server exposes 11 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
All 11 Greptile tools available for Vercel AI SDK
When Vercel AI SDK connects to Greptile through Vinkius, your AI agent gets direct access to every tool listed below — spanning codebase-intelligence, semantic-search, repository-indexing, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Delete indexed repository
Get file info
Check API usage
Get repository status
Index a repository
List indexed repositories
Query codebase with AI
Query with session context
Reindex a repository
Search in specific file
Search codebase
Connect Greptile to Vercel AI SDK via MCP
Follow these steps to wire Greptile into Vercel AI SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install dependencies
npm install @ai-sdk/mcp ai @ai-sdk/openaiReplace the token
[YOUR_TOKEN_HERE] with your Vinkius tokenRun the script
agent.ts and run with npx tsx agent.tsExplore tools
Why Use Vercel AI SDK with the Greptile MCP Server
Vercel AI SDK provides unique advantages when paired with Greptile through the Model Context Protocol.
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 Greptile integration everywhere
Built-in streaming UI primitives let you display Greptile tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Greptile + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Greptile MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Greptile in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Greptile tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Greptile capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Greptile through natural language queries
Example Prompts for Greptile in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Greptile immediately.
"How does the authentication middleware work in our backend repository?"
"Search for all files that import the database connection module and show me the file info."
"Index our new frontend repository and check the indexing status."
Troubleshooting Greptile MCP Server with Vercel AI SDK
Common issues when connecting Greptile to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpGreptile + Vercel AI SDK FAQ
Common questions about integrating Greptile MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
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?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.