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DeepSource MCP Server for Vercel AI SDK 14 tools — connect in under 2 minutes

Built by Vinkius GDPR 14 Tools SDK

The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect DeepSource through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.

Vinkius supports streamable HTTP and SSE.

typescript
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 DeepSource, list all available capabilities.",
    });
    console.log(text);
  } finally {
    await mcpClient.close();
  }
}

main();
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* 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 DeepSource MCP Server

Connect your DeepSource account to any AI agent and take full control of code quality analysis, vulnerability detection, and metrics monitoring through natural conversation.

The Vercel AI SDK gives every DeepSource tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 14 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

  • Code Issues — List and inspect code quality issues (code smells, anti-patterns, bugs) across repositories with severity and file locations
  • Analysis History — View recent analysis runs with status, branch, and analyzer information (Python, JavaScript, Go, etc.)
  • Security Vulnerabilities — Identify dependency vulnerabilities (SCA) with CVE IDs, CVSS scores, reachability, and fixability status
  • Code Metrics — Query maintainability index, cyclomatic complexity, lines of code, and test coverage percentages
  • Report Cards — Get overall repository health grades (A-F) with score breakdowns and trend analysis
  • SCA Targets — List all dependency manifest files being scanned for supply chain security
  • Repository Management — Activate/deactivate repos, update default branches, and regenerate DSN tokens

The DeepSource MCP Server exposes 14 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.

How to Connect DeepSource to Vercel AI SDK via MCP

Follow these steps to integrate the DeepSource MCP Server with Vercel AI SDK.

01

Install dependencies

Run npm install @ai-sdk/mcp ai @ai-sdk/openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the script

Save to agent.ts and run with npx tsx agent.ts

04

Explore tools

The SDK discovers 14 tools from DeepSource and passes them to the LLM

Why Use Vercel AI SDK with the DeepSource MCP Server

Vercel AI SDK provides unique advantages when paired with DeepSource through the Model Context Protocol.

01

TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box

02

Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same DeepSource integration everywhere

03

Built-in streaming UI primitives let you display DeepSource tool results progressively in React, Svelte, or Vue components

04

Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency

DeepSource + Vercel AI SDK Use Cases

Practical scenarios where Vercel AI SDK combined with the DeepSource MCP Server delivers measurable value.

01

AI-powered web apps: build dashboards that query DeepSource in real-time and stream results to the UI with zero loading states

02

API backends: create serverless endpoints that orchestrate DeepSource tools and return structured JSON responses to any frontend

03

Chatbots with tool use: embed DeepSource capabilities into conversational interfaces with streaming responses and tool call visibility

04

Internal tools: build admin panels where team members interact with DeepSource through natural language queries

DeepSource MCP Tools for Vercel AI SDK (14)

These 14 tools become available when you connect DeepSource to Vercel AI SDK via MCP:

01

activate_repository

Once activated, DeepSource will start analyzing the code on each push/PR. You must provide the repository ID (obtained from get_repository). Use this to enable code quality monitoring for a repository that was previously inactive. Activate a repository for code analysis in DeepSource

02

deactivate_repository

No new analyses will run until the repository is reactivated. You must provide the repository ID (obtained from get_repository). Use this to pause analysis for archived repositories or when you want to stop billing for a specific repository. Deactivate a repository to stop code analysis in DeepSource

03

get_report_card

This provides a quick health check of the repository's overall code quality status. You must provide the repository name, login, and VCS provider. Use this to get a high-level view of code quality trends and identify areas needing improvement. Get the overall report card (grade) for a repository

04

get_repository

You must provide the repository name, login (user or org name), and VCS provider (e.g., GITHUB, GITLAB, BITBUCKET). Use this to inspect repository configuration before querying issues, analyses, or metrics. Get details of a specific repository in DeepSource

05

get_repository_metrics

You must provide the repository name, login, and VCS provider. Optionally filter by specific metric shortcodes (e.g., "LCV" for line coverage, "MI" for maintainability index, "CC" for cyclomatic complexity). If no shortcodes specified, returns all available metrics with their values and thresholds. Get code quality metrics for a repository

06

get_test_coverage

Shows the coverage percentage value and any configured thresholds. You must provide the repository name, login, and VCS provider. Use this to monitor code quality and ensure adequate test coverage across your codebase. Get test coverage metrics for a repository

07

get_viewer

Use this to verify your API token is working and to get your user details from DeepSource. Get the authenticated user profile from DeepSource

08

get_vulnerability

You must provide the repository name, login, VCS provider, and the vulnerability occurrence ID (obtained from list_vulnerabilities). Use this to deep-dive into a specific vulnerability before deciding on remediation steps. Get details of a specific dependency vulnerability by its ID

09

list_analysis_runs

You must provide the repository name, login, and VCS provider. Optionally filter by branch name and limit the number of results (default: 20). Each run shows which analyzer was used (e.g., PYTHON, JAVASCRIPT, GO) and whether the analysis succeeded or failed. List recent code analysis runs for a repository

10

list_issues

You must provide the repository name, login, and VCS provider. Optionally filter by analyzer short code (e.g., "PYTHON", "JS-A1") and limit results (default: 50). Each issue includes up to 3 sample occurrences with file path and line number. Use this to identify code smells, anti-patterns, and potential bugs across your codebase. List code quality issues in a repository

11

list_sca_targets

Each target includes ecosystem (e.g., npm, pip, gem), package manager, manifest file path, and activation status. You must provide the repository name, login, and VCS provider. Use this to understand which dependency files are being scanned for vulnerabilities. List all SCA (Supply Chain Analysis) targets in a repository

12

list_vulnerabilities

Each vulnerability includes severity, CVE ID, CVSS score, description, affected package name and version, reachability status, and fixability. You must provide the repository name, login, and VCS provider. Optionally limit the number of results (default: 20). Use this to identify security risks in your dependencies and prioritize remediation. List dependency vulnerabilities in a repository (SCA)

13

regenerate_dsn

The DSN is used to authenticate DeepSource analysis runs. You must provide the repository ID (obtained from get_repository). This action invalidates the old DSN and returns the new one. Use this if you suspect the DSN has been compromised or needs rotation. Regenerate the DSN (Data Source Name) for a repository

14

update_default_branch

This affects which branch is analyzed by default. You must provide the repository ID (from get_repository) and the new branch name (e.g., "main", "develop", "master"). Use this when your team changes the default branch name (e.g., migrating from "master" to "main"). Update the default branch for a repository in DeepSource

Example Prompts for DeepSource in Vercel AI SDK

Ready-to-use prompts you can give your Vercel AI SDK agent to start working with DeepSource immediately.

01

"Show me the overall code quality report card and current issues for the 'api-service' repository in the 'acme-corp' GitHub organization."

02

"Check for any critical or high severity dependency vulnerabilities in the 'web-frontend' repo and tell me which packages are affected."

03

"What's the test coverage for our 'backend-api' repository and show me the most recent analysis runs?"

Troubleshooting DeepSource MCP Server with Vercel AI SDK

Common issues when connecting DeepSource to Vercel AI SDK through the Vinkius, and how to resolve them.

01

createMCPClient is not a function

Install: npm install @ai-sdk/mcp

DeepSource + Vercel AI SDK FAQ

Common questions about integrating DeepSource MCP Server with Vercel AI SDK.

01

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.
02

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.
03

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.

Connect DeepSource to Vercel AI SDK

Get your token, paste the configuration, and start using 14 tools in under 2 minutes. No API key management needed.