BugcrowdMCP: Server & Agents for the Bugcrowd API

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.

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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"

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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

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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

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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:

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

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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