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SlanyCukr

Bug Bounty MCP Server

by SlanyCukr

bugbounty_reconnaissance_workflow

Automates reconnaissance workflows for bug bounty hunting by gathering OSINT, testing vulnerabilities, and prioritizing security assessments based on target scope and domain.

Instructions

Create comprehensive reconnaissance workflow for bug bounty hunting.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
domainYes
out_of_scopeNo
program_typeNoweb
scopeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool handler function that executes the bugbounty_reconnaissance_workflow by proxying to the REST API backend.
    @mcp.tool()
    def bugbounty_reconnaissance_workflow(
        domain: str, scope: str = "", out_of_scope: str = "", program_type: str = "web"
    ) -> dict[str, Any]:
        """Create comprehensive reconnaissance workflow for bug bounty hunting."""
        data = {
            "domain": domain,
            "scope": scope.split(",") if scope else [],
            "out_of_scope": out_of_scope.split(",") if out_of_scope else [],
            "program_type": program_type,
        }
    
        logger.info(f"🎯 Creating reconnaissance workflow for {domain}")
        result = api_client.safe_post("api/bugbounty/reconnaissance-workflow", data)
    
        if result.get("success"):
            logger.info(f"✅ Reconnaissance workflow created for {domain}")
        else:
            logger.error(f"❌ Failed to create reconnaissance workflow for {domain}")
    
        return result
  • Backend REST API workflow handler for the /api/bugbounty/reconnaissance-workflow endpoint, which creates the reconnaissance workflow using the bugbounty_manager.
    @workflow()
    def create_reconnaissance_workflow():
        """Create comprehensive reconnaissance workflow for bug bounty hunting."""
        # Import here to avoid circular imports
        from src.rest_api_server.managers import BugBountyTarget, bugbounty_manager
    
        data = request.get_json()
    
        domain = data["domain"]
        scope = data.get("scope", [])
        out_of_scope = data.get("out_of_scope", [])
        program_type = data.get("program_type", "web")
    
        logger.info(f"Creating reconnaissance workflow for {domain}")
    
        # Create bug bounty target
        target = BugBountyTarget(
            domain=domain,
            scope=scope,
            out_of_scope=out_of_scope,
            program_type=program_type,
        )
    
        # Generate reconnaissance workflow
        workflow = bugbounty_manager.create_reconnaissance_workflow(target)
    
        logger.info(f"Reconnaissance workflow created for {domain}")
    
        return workflow
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'create' but doesn't clarify if this is a read-only planning tool or an executable workflow, what outputs or actions result, or any constraints like rate limits or permissions. The description is too high-level to inform the agent about the tool's operational behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the core action ('Create comprehensive reconnaissance workflow'). It avoids unnecessary words, but its brevity contributes to vagueness rather than clarity, as it lacks detail needed for effective tool use.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity implied by 'workflow' creation, 4 parameters with 0% schema coverage, no annotations, and an output schema (which the description doesn't reference), the description is incomplete. It doesn't explain what the tool outputs, how parameters interact, or behavioral traits, leaving significant gaps for the agent to infer usage.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter details. The description adds no information about parameters like 'domain,' 'out_of_scope,' 'program_type,' or 'scope,' leaving their purposes and formats unexplained. This fails to compensate for the lack of schema documentation, making parameter usage ambiguous.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states the tool 'Create[s] comprehensive reconnaissance workflow for bug bounty hunting,' which provides a general purpose (creating workflows) and domain context (bug bounty reconnaissance). However, it's vague about what constitutes a 'workflow' and doesn't distinguish it from sibling tools like 'bugbounty_osint_workflow' or 'analyze_target,' which may overlap in reconnaissance activities.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance is provided on when to use this tool versus alternatives. The description implies usage for bug bounty reconnaissance but doesn't specify scenarios, prerequisites, or exclusions. With many sibling tools focused on scanning and analysis, the lack of differentiation leaves the agent without clear selection criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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