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danielbres

massive-mcp

by danielbres

get_last_trade

Retrieve the most recent trade data for a stock by providing its ticker symbol.

Instructions

Most recent trade for a stock.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock symbol.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The actual handler/definition of the 'get_last_trade' tool. It is an async function registered via @mcp.tool() that takes a ticker string and calls client.get(f"/v2/last/trade/{ticker}") to fetch the most recent trade for a stock.
    @mcp.tool()
    async def get_last_trade(ticker: str) -> dict[str, Any]:
        """Most recent trade for a stock.
    
        Args:
            ticker: Stock symbol.
        """
        return await client.get(f"/v2/last/trade/{ticker}")
  • The registration location where the quotes module (containing get_last_trade) is registered via module.register(mcp, client).
    for module in (
        aggregates,
        quotes,
        snapshots,
        tickers,
        news,
        reference,
        indicators,
        corporate,
        financials,
    ):
        module.register(mcp, client)
  • The schema is implicit via the decorator. Input: ticker (str). Output: dict[str, Any].
    @mcp.tool()
    async def get_last_trade(ticker: str) -> dict[str, Any]:
        """Most recent trade for a stock.
    
        Args:
            ticker: Stock symbol.
        """
        return await client.get(f"/v2/last/trade/{ticker}")
  • MassiveClient.get is the helper that executes the HTTP request to the Massive API.
    async def get(
        self, path: str, params: dict[str, Any] | None = None, *, trim: bool = True
    ) -> dict[str, Any]:
        merged: dict[str, Any] = {k: v for k, v in (params or {}).items() if v is not None}
        if self._settings.auth_mode == "query":
            merged["apiKey"] = self._settings.api_key
    
        last_exc: Exception | None = None
        for attempt in range(MAX_RETRIES):
            try:
                resp = await self._http.get(path, params=merged)
            except httpx.HTTPError as exc:
                last_exc = exc
                await asyncio.sleep(2**attempt)
                continue
    
            if resp.status_code == 429:
                retry_after = float(resp.headers.get("Retry-After", 2**attempt))
                await asyncio.sleep(min(retry_after, 30))
                continue
            if 500 <= resp.status_code < 600 and attempt < MAX_RETRIES - 1:
                await asyncio.sleep(2**attempt)
                continue
    
            if resp.status_code == 401:
                hint = (
                    "auth rejected — verify MASSIVE_API_KEY; "
                    "if you used MASSIVE_AUTH_MODE=bearer, try 'query' (or vice versa)"
                )
                raise MassiveAPIError(401, hint, _strip_secrets(str(resp.request.url)))
    
            try:
                data = resp.json()
            except ValueError:
                data = {"raw": resp.text}
    
            if not resp.is_success:
                msg = data.get("error") or data.get("message") or resp.reason_phrase or "request failed"
                raise MassiveAPIError(resp.status_code, str(msg), _strip_secrets(str(resp.request.url)))
    
            return _trim(data) if trim else data
    
        raise MassiveAPIError(0, f"network error after {MAX_RETRIES} retries: {last_exc}", path)
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. It does not disclose behavioral traits such as data freshness, scope, or that it returns the single latest trade. The minimal text lacks context beyond the basic action.

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 extremely concise at 6 words, with no wasted text. While efficient, it could benefit from slightly more detail without losing brevity.

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 has an output schema (not shown) and a single required parameter, the description is minimally adequate. However, it does not mention what the output contains (e.g., price, time, volume) or any limitations, leaving room for improvement.

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

Parameters3/5

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

Schema description coverage is 100% with ticker described as 'Stock symbol.' The description adds no new meaning beyond the schema, which already clearly defines the parameter. Baseline score of 3 applies.

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 'Most recent trade for a stock.' clearly states the verb (get) and resource (most recent trade), and distinguishes from siblings like get_trades (multiple trades) and get_last_quote (quote).

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

Usage Guidelines3/5

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

The description provides no explicit guidance on when to use this tool over alternatives. Usage is implied by the purpose but not stated.

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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