How to Use the DeepSource MCP in AutoGen

Q: Can AutoGen agents toggle DeepSource repository monitoring?

Yes, agents can call deactivaterepository or activaterepository during their conversation. This is useful when a management agent decides to archive a repository based on team consensus.

Q: How do AutoGen agents handle DeepSource DSN rotations?

A security agent can call regeneratedsn if it detects a potential credential leak. The agent then passes the new DSN to your deployment agent to update the repository's build pipeline environment variables.

Q: What happens if an AutoGen agent fails to fetch DeepSource metrics?

If getrepositorymetrics returns an error, your AutoGen agents will discuss the failure in their chat history. They can fallback to calling getreportcard to get a high-level grade instead.

Let your AutoGen agents debate code quality and security risks using real-time telemetry from DeepSource.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect DeepSource MCP to AutoGen

Create your Vinkius account to connect DeepSource to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup DeepSource with AutoGen

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Let AutoGen agents debate code quality grades

The `get_report_card` tool feeds the overall quality grade of a repository into your AutoGen multi-agent chat. A quality-assurance agent can use this grade to challenge a developer agent's proposal to merge a pull request. If the grade is low, the QA agent calls `list_issues` to extract the specific code smells blocking the merge. The agents then negotiate which issues must be resolved immediately and which can be deferred to a later sprint.

Resolve security alerts via AutoGen multi-agent consensus

The `list_vulnerabilities` tool provides a list of dependency risks that your AutoGen security agent can analyze via this MCP Server. This agent debates with your dependency-manager agent about whether a CVSS score warrants an immediate patch. To settle the debate, the security agent calls `get_vulnerability` to check the reachability of the risk. Once they agree on the severity, the agents collaborate to draft a pull request updating the manifest files.

Coordinate repository settings with this MCP Server

The `update_default_branch` tool allows your release coordinator agent to update repository configurations automatically. When a release cycle ends, this agent coordinates with your testing agent to shift the target branch. Before making the change, the testing agent calls `list_analysis_runs` to ensure all recent builds on the new branch succeeded. If any run failed, the agents halt the branch update and notify the team.

Setup guide

Set up DeepSource MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes DeepSource tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="DeepSource_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent DeepSource data")
print(result.messages[-1].content)

Get your connection token →

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="DeepSource_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent DeepSource data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DeepSource. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect DeepSource now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about DeepSource MCP in AutoGen

You use the MCP tools adapter to convert the server's tools for AutoGen. This lets you pass tools like `list_issues` directly to your `AssistantAgent` constructor.

Yes, agents can call `deactivate_repository` or `activate_repository` during their conversation. This is useful when a management agent decides to archive a repository based on team consensus.

A security agent can call `regenerate_dsn` if it detects a potential credential leak. The agent then passes the new DSN to your deployment agent to update the repository's build pipeline environment variables.

If `get_repository_metrics` returns an error, your AutoGen agents will discuss the failure in their chat history. They can fallback to calling `get_report_card` to get a high-level grade instead.

This MCP Server keeps your code issue lists and branch configurations isolated within a secure V8 sandbox. Vinkius manages the authentication token securely, ensuring your raw source code details are never exposed to external LLM logging platforms.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python

Vercel AI SDK sdk-typescript