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danielbres

massive-mcp

by danielbres

get_quotes

Fetch historical NBBO stock quotes with optional date range and pagination.

Instructions

Historical NBBO quotes for a stock.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesStock symbol.
timestamp_gteNoInclusive lower bound ("YYYY-MM-DD" or ns/ms unix).
timestamp_ltNoExclusive upper bound.
limitNoMax rows (Massive cap typically 50000). Default 50.
cursorNoPagination cursor from a previous `next_cursor`.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • Handler function that fetches historical NBBO quotes for a stock ticker via Massive API /v3/quotes/{ticker}.
    async def get_quotes(
        ticker: str,
        timestamp_gte: str | None = None,
        timestamp_lt: str | None = None,
        limit: int = 50,
        cursor: str | None = None,
    ) -> dict[str, Any]:
        """Historical NBBO quotes for a stock.
    
        Args:
            ticker: Stock symbol.
            timestamp_gte: Inclusive lower bound ("YYYY-MM-DD" or ns/ms unix).
            timestamp_lt: Exclusive upper bound.
            limit: Max rows (Massive cap typically 50000). Default 50.
            cursor: Pagination cursor from a previous `next_cursor`.
        """
        return await client.get(
            f"/v3/quotes/{ticker}",
            {
                "timestamp.gte": timestamp_gte,
                "timestamp.lt": timestamp_lt,
                "limit": limit,
                "cursor": cursor,
            },
        )
  • The register() function decorates tool handlers with @mcp.tool(), including get_quotes. This is where get_quotes is registered as an MCP tool.
    def register(mcp: FastMCP, client: MassiveClient) -> None:
        @mcp.tool()
  • The build_server() function iterates over tool modules (including 'quotes') and calls module.register(mcp, client) to register all tools including get_quotes.
    for module in (
        aggregates,
        quotes,
        snapshots,
        tickers,
        news,
        reference,
        indicators,
        corporate,
        financials,
    ):
        module.register(mcp, client)
Behavior2/5

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

No annotations exist, so the description carries full burden. It fails to mention pagination, rate limits, auth needs, or behavior for missing stocks. Only states it returns historical quotes.

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

Conciseness3/5

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

A single sentence is concise but under-specifies the tool. It front-loads the resource, but omits necessary behavioral and usage details.

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?

With 5 parameters and output schema, the description is too minimal. Missing details on NBBO meaning, time range behavior, pagination, and differentiation from sibling tools.

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 coverage is 100%, so parameters are fully described in the schema. The description adds no extra parameter context beyond indicating historical time range, which is already implied by timestamp fields.

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 'Historical NBBO quotes for a stock' clearly identifies the resource (historical NBBO quotes) and the implied action (get). It distinguishes from siblings like get_last_quote (single quote) and get_trades (trades), though not explicitly.

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 on when to use this tool versus alternatives like get_last_quote or get_trades. No mention of prerequisites, best practices, or scenarios.

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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