Skip to main content
Glama

remove_from_watchlist

Remove a stock symbol from your watchlist to declutter your portfolio tracking and focus on relevant assets.

Instructions

Removes a symbol from the watchlist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The core handler function for the 'remove_from_watchlist' tool. It uppercases the symbol, loads the watchlist from JSON, removes the symbol if present, saves the updated list, and returns a confirmation message.
    def remove_from_watchlist(symbol: str) -> str:
        """
        Removes a symbol from the watchlist.
        """
        symbol = symbol.upper()
        watchlist = _load_watchlist()
        if symbol in watchlist:
            watchlist.remove(symbol)
            _save_watchlist(watchlist)
            logger.info(f"Removed {symbol} from watchlist")
            return f"Removed {symbol} from watchlist."
        return f"{symbol} was not in the watchlist."
  • server.py:410-413 (registration)
    MCP tool registration block in the FastMCP server where remove_from_watchlist is registered via the register_tools helper function.
    register_tools(
        [add_to_watchlist, remove_from_watchlist],
        "Watchlist"
    )
  • Helper function to persist the watchlist to JSON file, used by remove_from_watchlist.
    def _save_watchlist(watchlist: List[str]):
        with open(WATCHLIST_FILE, "w") as f:
            json.dump(watchlist, f, indent=4)
  • Helper function to load the watchlist from JSON file, used by remove_from_watchlist.
    def _load_watchlist() -> List[str]:
        if not WATCHLIST_FILE.exists():
            return []
        try:
            with open(WATCHLIST_FILE, "r") as f:
                return json.load(f)
        except Exception:
            return []
  • server.py:20-20 (registration)
    Import statement in MCP server bringing in the remove_from_watchlist function for registration.
    from tools.watchlist import add_to_watchlist, remove_from_watchlist, get_watchlist_data
Behavior2/5

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

No annotations are provided, so the description carries full burden. It states the action is a removal, implying a destructive mutation, but doesn't disclose behavioral traits such as permissions needed, whether the operation is reversible, error handling (e.g., if symbol isn't in watchlist), or rate limits. This leaves significant gaps for an agent to understand the tool's behavior.

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, clear sentence with zero waste—it directly states the tool's action and target. It's appropriately sized for a simple tool and front-loaded with the essential information, making it highly concise and well-structured.

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

Completeness3/5

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

Given the tool's low complexity (1 parameter, no annotations, but has an output schema), the description is minimally complete. It states what the tool does, but lacks details on usage, parameters, and behavioral context. The output schema may cover return values, but the description doesn't provide enough guidance for effective use, making it adequate but with clear gaps.

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?

The input schema has 1 parameter with 0% description coverage, and the tool description doesn't add any semantic details about the 'symbol' parameter. It doesn't explain what format the symbol should be in (e.g., ticker symbol like 'AAPL'), examples, or constraints. With low schema coverage, the description fails to compensate, leaving the parameter poorly documented.

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 action ('removes') and resource ('a symbol from the watchlist'), which is clear but basic. It doesn't differentiate from sibling tools like 'add_to_watchlist' beyond the verb, and lacks specificity about what type of watchlist or symbols are involved (e.g., stocks, crypto). This makes it vague in context.

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. It doesn't mention prerequisites (e.g., the symbol must already be in the watchlist), exclusions, or related tools like 'add_to_watchlist' for managing the watchlist. The description is standalone with no contextual usage hints.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/N-lia/MonteWalk'

If you have feedback or need assistance with the MCP directory API, please join our Discord server