Bugcrowd MCP Server

A high-performance MCP (Model Context Protocol) server that provides secure, tool-based access to the Bugcrowd API, allowing for natural language interaction through various AI agent platforms.

Features

Broad API Coverage: Provides tools for interacting with Organizations, Programs, Submissions, Assets, and more.
Multi-Agent Support: Includes ready-to-use agents for OpenAI, Anthropic (Claude), Google (Gemini), and FastMCP.
Extensible & Customizable: Easily switch between AI providers, configure different models, and integrate with platform-specific CLIs.
Secure: Uses environment variables for API credentials and performs input validation.
Dynamic Help: Includes a help() tool that provides real-time documentation for all available tools.

Quick Start

This guide will get you up and running with the default agent (openai).

1. Prerequisites

Python 3.10+
uv for package installation.

2. Installation

Clone the repository, create a virtual environment, and install dependencies.

git clone https://github.com/unstrike/Bugcrowd_MCP_Server.git
cd Bugcrowd_MCP_Server

# Create and activate virtual environment
uv venv
source .venv/bin/activate

# Install dependencies
uv sync

3. Configuration

Export your Bugcrowd and OpenAI API credentials as environment variables.

export BUGCROWD_API_USERNAME="your-username"
export BUGCROWD_API_PASSWORD="your-password"
export OPENAI_API_KEY="your-openai-api-key"

4. Run the Agent

Start the interactive agent.

uv run python -m bugcrowd_agents.agent_orchestrator

You can now interact with the Bugcrowd API using natural language.

Example Prompts:

"Show me available bug bounty programs"
"What are the 5 most recent vulnerability submissions?"
"Use the help tool to see all available commands"

Advanced Usage

Switching Agents

The true power of this server lies in its flexibility. You can easily switch between supported AI platforms by setting the AGENT_PLATFORM environment variable.

Supported platforms: openai (default), claude, gemini, fastmcp.

Remember to set the appropriate API key for the agent you choose.

Example: Running the Gemini Agent

# 1. Set the API key for Google
export GOOGLE_AI_API_KEY="your-gemini-api-key"

# 2. Run the orchestrator with the AGENT_PLATFORM variable
AGENT_PLATFORM=gemini uv run python -m bugcrowd_agents.agent_orchestrator

Example: Running the Claude Agent

export ANTHROPIC_API_KEY="your-claude-api-key"
AGENT_PLATFORM=claude uv run python -m bugcrowd_agents.agent_orchestrator

Using the FastMCP Agent

The fastmcp agent is a versatile client that can use different LLM backends. Configure it by setting the FASTMCP_PROVIDER environment variable.

Supported providers: anthropic (default), google, openai.

Example: Running FastMCP with the Google (Gemini) Backend

# 1. Set the API key for the desired backend
export GOOGLE_AI_API_KEY="your-gemini-api-key"

# 2. Set the platform and provider, then run
AGENT_PLATFORM=fastmcp FASTMCP_PROVIDER=google uv run python -m bugcrowd_agents.agent_orchestrator

Customizing Agent Models

You can override the default models for each agent by setting environment variables:

Claude: CLAUDE_MAIN_MODEL, CLAUDE_SUMMARY_MODEL
Gemini: GEMINI_MAIN_MODEL, GEMINI_SUMMARY_MODEL
OpenAI: OPENAI_MODEL

Available Tools

The server provides the following tools. For detailed parameter information, run the agent and use the help() tool (e.g., help('get_submission')).

Category	Tool	Description
Organizations	`get_organizations`	List all accessible organizations
	`get_organization`	Get specific organization details
Programs	`get_programs`	List bug bounty programs
	`get_program`	Get specific program details
Submissions	`get_submissions`	List vulnerability submissions
	`get_submission`	Get specific submission details
	`create_submission`	Create a new vulnerability report
	`update_submission`	Update an existing submission
	`create_comment`	Add a comment to a submission
Teams	`get_teams`	List all teams in an organization
	`create_team`	Create a new team
	`delete_team`	Delete a team
Rewards	`get_monetary_rewards`	List bounty rewards
	`create_monetary_reward`	Create a new monetary reward
	`update_monetary_reward`	Update an existing monetary reward
Users	`get_users`	List users in an organization
	`get_user`	Get specific user details
Health	`server_health`	Check server and API connectivity
Help	`help`	Get detailed help for any tool

Direct Integration

For integration with platform-specific CLIs (bypassing the included agent handlers), use the provided configuration templates.

For OpenAI (codex): Use docs/config.toml.
For Gemini, Claude, etc.: Use docs/config.json.

Instructions:

Copy the appropriate template file to your tool's configuration directory (e.g., ~/.codex/config.toml).
In the copied file, update the cwd variable to the absolute path of the Bugcrowd_MCP_Server project directory.

Documentation

API Reference: A static reference for all tool and endpoint details.
Architecture Diagram: An overview of the system architecture.
Bugcrowd REST API: The official API documentation that this server is built upon.

For more detailed information on MCP server configuration, refer to the official documentation for your platform:

OpenAI: Codex MCP Server Configuration
Google Gemini: Configure MCP Servers
Anthropic Claude: MCP for Claude
FastMCP: JSON Configuration and Running a Server

Bugcrowd MCP Server