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list_saved_quereis

Retrieve stored BloodHound queries for Active Directory penetration testing to analyze attack paths and identify vulnerabilities during security assessments.

Instructions

list already saved queries in bloodhound

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • MCP tool registration and handler function for 'list_saved_quereis'. This thin wrapper delegates the execution to the bloodhound.list_saved_queries() helper function.
    @mcp.tool(name="list_saved_quereis",description="list already saved queries in bloodhound")
    def list_saved_queries():
        return bloodhound.list_saved_queries()
  • The core helper function that implements the logic: creates authenticated BloodHound client and performs GET request to /api/v2/saved-queries endpoint to list saved queries.
    def list_saved_queries():
        credentials = Credentials(
            token_id=config.BHE_TOKEN_ID,
            token_key=config.BHE_TOKEN_KEY,
        )
    
        client = Client(scheme=BHE_SCHEME, host=config.BHE_DOMAIN, port=config.BHE_PORT, credentials=credentials)
        response=client._request("GET","/api/v2/saved-queries")
        return response.json()
Behavior2/5

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

With no annotations provided, the description carries full burden but offers minimal behavioral insight. It states what the tool does but doesn't disclose whether it requires authentication, returns structured data, handles errors, or has any side effects. For a tool with zero annotation coverage, this is inadequate.

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

Conciseness5/5

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

The description is a single, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly.

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 lack of annotations and output schema, the description is insufficient. It doesn't explain what the output looks like (e.g., list format, error handling) or behavioral constraints. For a tool in a security context (BloodHound), more context on permissions or data sensitivity would be helpful.

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

Parameters4/5

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

The tool has 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not introducing confusion or redundancy.

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

Purpose4/5

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

The description clearly states the verb ('list') and resource ('already saved queries in bloodhound'), making the purpose immediately understandable. It doesn't explicitly differentiate from siblings like 'run_bloodhound_query' or 'test_bloodhound_connection', but the specificity of 'saved queries' provides inherent distinction.

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 guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing an active BloodHound connection) or contrast with similar tools like 'run_bloodhound_query' for executing queries versus listing saved ones.

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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