Skip to main content
Glama
78degrees

QuantRisk-MCP-Server

by 78degrees
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Local

stress_test

Stress test a portfolio against historical crises or custom shocks to quantify downside risk.

Instructions

Stress test a portfolio against historical crisis scenarios (GFC 2008, COVID 2020, etc.) or custom shocks (paid tier).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionsYesArray of portfolio positions. Free tier: max 20 positions and historical scenarios only. Paid tier: up to 500 positions plus custom shocks.
scenariosNoHistorical scenarios to run. Available values: gfc_2008, covid_2020, dot_com_2000, black_monday_1987, taper_tantrum_2013, rate_hike_2022, volmageddon_2018, euro_crisis_2011. Default: [gfc_2008, covid_2020].
custom_shocksNoCustom shock definitions. PAID tier only. Each shock specifies ticker-level, sector-level, or market-wide price changes.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations, the description carries full burden but only mentions tier restrictions. It does not disclose whether the operation is read-only, destructive, or requires specific permissions. Behavioral traits beyond the schema are minimal.

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, concise sentence that immediately conveys the tool's core function. No wasted words.

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?

The tool has 3 parameters and no output schema. While parameters are well-described in the schema, the description does not explain what the tool returns (e.g., P&L impact, risk metrics) or how the output should be interpreted. This leaves a gap for an AI agent.

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?

Schema coverage is 100%, so baseline is 3. The description adds value by summarizing the two main parameter categories (historical scenarios vs custom shocks) and mentioning the paid tier limitation, which is not in the schema.

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 clearly states the action (stress test), resource (portfolio), and context (historical crisis scenarios or custom shocks). It is specific but does not explicitly differentiate from sibling tools like monte_carlo_simulation or analyze_risk.

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, nor any prerequisites or limitations beyond paying for custom shocks. The description lacks context for tool selection.

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

Deploy Server

Other Tools