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get_workspace_details

Retrieve current BitScale workspace details including plan, credit balances, people/company search limits, and member counts.

Instructions

Get details about the current BitScale workspace — plan info, credit balances, people/company search limits, and member counts.

The workspace is identified automatically from the API key configured during MCP setup. No parameters needed.

Returns: workspace id, name, plan (name, credits_included, billing_interval, next_billing_date, price), credits (total, used, remaining, plan_credits, rollover, topup), people_company_searches (limit, used, remaining), and members (total, owners, admins, editors).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • main.py:68-83 (handler)
    The handler function for the 'get_workspace_details' tool. Decorated with @mcp.tool(), it calls the BitScale API GET /workspace endpoint and returns the JSON result containing plan info, credit balances, search limits, and member counts.
    @mcp.tool()
    def get_workspace_details() -> str:
        """
        Get details about the current BitScale workspace — plan info, credit
        balances, people/company search limits, and member counts.
    
        The workspace is identified automatically from the API key configured
        during MCP setup. No parameters needed.
    
        Returns: workspace id, name, plan (name, credits_included, billing_interval,
        next_billing_date, price), credits (total, used, remaining, plan_credits,
        rollover, topup), people_company_searches (limit, used, remaining),
        and members (total, owners, admins, editors).
        """
        data = _get("/workspace")
        return json.dumps(data, indent=2)
  • main.py:47-53 (helper)
    The _get() helper function performs the authenticated GET request to the BitScale API, used by get_workspace_details.
    def _get(path: str, params: dict | None = None, timeout: int = 30) -> dict:
        """Perform an authenticated GET request against the BitScale API."""
        url = f"{BITSCALE_API_BASE}{path}"
        with httpx.Client(timeout=timeout) as client:
            response = client.get(url, headers=_headers(), params=params)
        response.raise_for_status()
        return response.json()
  • main.py:34-44 (helper)
    The _headers() helper function builds the authentication headers using the API key.
    def _headers() -> dict:
        """Return the auth headers required by the BitScale API."""
        if not API_KEY:
            raise RuntimeError(
                "BITSCALE_API_KEY environment variable is not set. "
                "Set it before starting the server."
            )
        return {
            "X-API-KEY": API_KEY,
            "Content-Type": "application/json",
        }
  • main.py:68-83 (registration)
    The @mcp.tool() decorator on line 68 registers 'get_workspace_details' as an MCP tool with the FastMCP server.
    @mcp.tool()
    def get_workspace_details() -> str:
        """
        Get details about the current BitScale workspace — plan info, credit
        balances, people/company search limits, and member counts.
    
        The workspace is identified automatically from the API key configured
        during MCP setup. No parameters needed.
    
        Returns: workspace id, name, plan (name, credits_included, billing_interval,
        next_billing_date, price), credits (total, used, remaining, plan_credits,
        rollover, topup), people_company_searches (limit, used, remaining),
        and members (total, owners, admins, editors).
        """
        data = _get("/workspace")
        return json.dumps(data, indent=2)
Behavior4/5

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

The description lists the returned fields in detail, implying a read-only operation. No annotations are provided, so the description carries the full burden. It is transparent but could mention any side effects or permissions.

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 efficiently structured with a brief purpose statement followed by a bulleted list of returned fields. Every sentence is informative with no redundancy.

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

Completeness5/5

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

Given zero parameters and detailed output description, the description covers all necessary context for an agent to invoke the tool and interpret results. No gaps are apparent.

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?

Zero parameters are defined, and the description justifies why no parameters are needed (automatic workspace identification). This adds meaning beyond the empty schema.

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

Purpose5/5

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

The description clearly states the tool retrieves details about the current BitScale workspace, including specific categories like plan info, credit balances, and member counts. It is distinct from sibling tools that deal with grids, runs, or API keys.

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

Usage Guidelines4/5

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

The description explains that no parameters are needed and the workspace is identified automatically from the API key. While it does not explicitly contrast with sibling tools, the context makes its use case clear.

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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