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DeepSource MCP Server for OpenAI Agents SDK 14 tools — connect in under 2 minutes

Built by Vinkius GDPR 14 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect DeepSource through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="DeepSource Assistant",
            instructions=(
                "You help users interact with DeepSource. "
                "You have access to 14 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from DeepSource"
        )
        print(result.final_output)

asyncio.run(main())
DeepSource
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 OpenAI Agents SDK auto-discovers all 14 tools from DeepSource through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries DeepSource, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the DeepSource MCP Server with OpenAI Agents SDK.

01

Install the SDK

Run pip install openai-agents in your Python environment

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

03

Run the script

Save the code above and run it: python agent.py

04

Explore tools

The agent will automatically discover 14 tools from DeepSource

Why Use OpenAI Agents SDK with the DeepSource MCP Server

OpenAI Agents SDK provides unique advantages when paired with DeepSource through the Model Context Protocol.

01

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

02

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

03

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

04

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

DeepSource + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the DeepSource MCP Server delivers measurable value.

01

Automated workflows: build agents that query DeepSource, process the data, and trigger follow-up actions autonomously

02

Multi-agent orchestration: create specialist agents. one queries DeepSource, another analyzes results, a third generates reports

03

Data enrichment pipelines: stream data through DeepSource tools and transform it with OpenAI models in a single async loop

04

Customer support bots: agents query DeepSource to resolve tickets, look up records, and update statuses without human intervention

DeepSource MCP Tools for OpenAI Agents SDK (14)

These 14 tools become available when you connect DeepSource to OpenAI Agents 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents 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 OpenAI Agents SDK

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

01

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents
02

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

DeepSource + OpenAI Agents SDK FAQ

Common questions about integrating DeepSource MCP Server with OpenAI Agents SDK.

01

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.
02

Can I use multiple MCP servers in one agent?

Yes. Pass a list of MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.
03

Does the SDK support streaming responses?

Yes. The SDK supports SSE and Streamable HTTP transports, both of which work natively with Vinkius.

Connect DeepSource to OpenAI Agents SDK

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