Can the AI Agent resolve or close a task automatically?

Yes, using the `update_task` tool, the agent can change the task status to 'closed' or 'done' within BugHerd.

Are attachments or screenshots supported?

Currently, the MCP Server manages text-based tasks, comments, and project structures. Adding direct screenshot files via AI is not supported in this version.

Can I read comments from any ticket?

Yes! The agent can fetch and read all comments attached to a specific task using the `list_comments` tool, provided you supply the Project ID and Task ID.

INSTANT PLUG AND PLAY

BugHerd MCP Server for CrewAIGive CrewAI instant access to 10 tools to Add Comment, Create Project, Create Task, and more

Name: BugHerd
Availability: InStock
Author: Vinkius

Built by Vinkius GDPR 10 Tools Framework

Connect your CrewAI agents to BugHerd through Vinkius, pass the Edge URL in the `mcps` parameter and every BugHerd tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

Use with Your AI Agent

Ask AI about this App Connector for CrewAI

Open in ChatGPT Open in Claude Open in Perplexity

The BugHerd app connector for CrewAI is a standout in the Developer Tools category — giving your AI agent 10 tools to work with, ready to go from day one.

Vinkius delivers Streamable HTTP and SSE to any MCP client

python

from crewai import Agent, Task, Crew

agent = Agent(
    role="BugHerd Specialist",
    goal="Help users interact with BugHerd effectively",
    backstory=(
        "You are an expert at leveraging BugHerd tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token. get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in BugHerd "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 10 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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 BugHerd MCP Server

O que você pode fazer

Create and list your BugHerd projects.
Manage tasks seamlessly inside projects.
Retrieve, add, and monitor comments on specific bug tasks.
View all members within your BugHerd workspace.

Como funciona

1. Install the BugHerd MCP Server on your Vinkius Edge. 2. Add your personal BugHerd API key in the credentials page. 3. Empower your AI agent to fetch bugs, add comments, and triage tickets naturally via chat.

Para quem é?

Ideal for development and QA teams looking to interact with BugHerd tickets directly via Cursor, Claude, or any MCP-enabled agent. Turn your AI into a full-fledged QA assistant.

When paired with CrewAI, BugHerd becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call BugHerd tools autonomously, one agent queries data, another analyzes results, a third compiles reports, all orchestrated through Vinkius with zero configuration overhead.

The BugHerd MCP Server exposes 10 tools through the Vinkius. Connect it to CrewAI in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

All 10 BugHerd tools available for CrewAI

When CrewAI connects to BugHerd through Vinkius, your AI agent gets direct access to every tool listed below — spanning bug-tracking, website-feedback, task-management, 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.

add_comment

Add a comment to a BugHerd task

create_project

Create a new project in BugHerd

create_task

Create a new task in a BugHerd project

get_project

Get a specific project in BugHerd

get_task

Get a specific task in BugHerd

list_comments

List comments on a BugHerd task

list_projects

List projects in BugHerd

list_tasks

List tasks for a project in BugHerd

list_users

List users in the BugHerd account

update_task

Can update description, status, priority, or assigned_to_id. Update a task in BugHerd

Connect BugHerd to CrewAI via MCP

Follow these steps to wire BugHerd into CrewAI. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.

Install CrewAI

Run pip install crewai

Replace the token

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

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py. CrewAI auto-discovers 10 tools from BugHerd

Why Use CrewAI with the BugHerd MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with BugHerd through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles, one agent researches, another analyzes, a third generates reports, each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

BugHerd + CrewAI Use Cases

Practical scenarios where CrewAI combined with the BugHerd MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries BugHerd for raw data, then a second analyst agent cross-references findings and flags anomalies. all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries BugHerd, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain BugHerd tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries BugHerd against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Example Prompts for BugHerd in CrewAI

Ready-to-use prompts you can give your CrewAI agent to start working with BugHerd immediately.

"List all active projects in BugHerd."

"Create a new bug task in project 123 saying 'Login button is broken'."

"Read the comments on task 456 in project 123."

Troubleshooting BugHerd MCP Server with CrewAI

Common issues when connecting BugHerd to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts. check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

BugHerd + CrewAI FAQ

Common questions about integrating BugHerd MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily. when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.