quantra-mcp

by joseprupi

Overview Schema Source Related Servers Discussions Admin

Python

Hybrid

price_vanilla_swap

Price fixed-vs-IBOR swaps by providing market data and trade details to calculate NPV, fair rate, and leg cash flows.

Instructions

Price a fixed-vs-IBOR swap (POST /price-vanilla-swap).

Args: market_data_source: where the market numbers in this call come from. user_pasted (the user pasted or typed the numbers in this conversation), user_file (the user attached a file/screenshot the numbers were read from), engine_example (an engine example's pricing block, only when the user explicitly asked to run an example), session (a market previously stored in this session, which itself came from one of the above). There is no value for estimated, recalled or placeholder data. If you would have to invent numbers, do not call this tool: ask the user for the data. market: {"session": name}, an engine pricing block (used verbatim) or {curves: [...], indices: [...]} (build_curve results allowed). preset: a preset with a vanilla_swap block (EUR_EURIBOR_6M, EUR_EURIBOR_3M): schedule, fixed and floating leg conventions. swap_type: Payer (pay fixed) or Receiver. notional: constant notional (> 0). fixed_rate: decimal, e.g. 0.032. effective_date: YYYY-MM-DD or spot (as_of + the preset's settlement days, resolved by the engine's /calendar-advance). discounting_curve, forwarding_curve: curve ids in the market. termination_date: YYYY-MM-DD; or give tenor (5Y, resolved by the engine from the effective date, Unadjusted). spread: floating-leg spread (decimal, default 0.0). index_id: floating index id in the market (default: the preset's index id). fixed_leg_overrides, floating_leg_overrides: replace conventions (frequency, day_counter, payment_convention, notionals, schedule rules). additional_trades: more swaps for the same request (same preset/market). as_of: YYYY-MM-DD; required unless market is a pricing block. include_flows: ask the engine for per-leg cash flows.

Result: uniform shape + notes (every convention with its source), date_resolution (the /calendar-advance calls) and summary.swaps (npv, fair_rate, leg npvs selected from the response).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`as_of`	No
`tenor`	No
`market`	Yes
`preset`	Yes
`spread`	No
`index_id`	No
`notional`	Yes
`swap_type`	Yes
`fixed_rate`	Yes
`request_id`	No
`include_flows`	No
`effective_date`	Yes
`forwarding_curve`	Yes
`termination_date`	No
`additional_trades`	No
`discounting_curve`	Yes
`calendar_overrides`	No
`market_data_source`	Yes
`fixed_leg_overrides`	No
`floating_leg_overrides`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.4Oct 7, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses market-data provenance rules, the /calendar-advance date resolution, defaults (spread 0.0, preset index), and the response shape (notes, date_resolution, summary.swaps). It stops short of stating the operation is side-effect free/read-only or whether it requires session state or auth, which an annotation would normally cover.

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?

Purpose is front-loaded and the Args block is well structured with each line earning its place given the 0% schema coverage. The trailing "Result" paragraph is mildly redundant since an output schema exists, and the block is long, but length here is justified by parameter breadth.

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

Completeness4/5

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

For a 20-parameter, nested-object, packed-structure tool the description is nearly complete: provenance, dates, curves, overrides, batching, and return shape are all covered. Remaining gaps are the unmentioned request_id/calendar_overrides and the absence of any pointer to related tools (fair_rate, swap_dv01, reprice_with) an agent might need next.

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

Parameters5/5

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

Schema description coverage is 0% but the Args block documents the overwhelming majority of the 20 parameters with formats, defaults, and value semantics (e.g. fixed_rate "decimal, e.g. 0.032", effective_date "spot", swap_type Payer/Receiver, overrides meaning, additional_trades batching). Only request_id and calendar_overrides go unmentioned, which is a trivial gap given the otherwise dense compensation.

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?

Opens with a specific verb+resource ("Price a fixed-vs-IBOR swap") plus the underlying endpoint, which cleanly separates it from the sibling pricing tools like price_ois_swap and price_fra. An agent knows exactly what instrument is being valued without opening the schema.

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?

Strong conditional guidance for market_data_source (user_pasted vs user_file vs engine_example vs session) and an explicit when-not: "If you would have to invent numbers, do not call this tool: ask the user for the data." However it never routes to alternative pricing siblings such as fair_rate, swap_dv01, or reprice_with, so cross-tool selection is left implicit.

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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