portfolio-mcp

update_portfolio_weights

Update the weight distribution of assets in a portfolio and recalculate performance metrics such as Sharpe ratio.

Instructions

Update the allocation weights of an existing portfolio.

Changes the weight distribution across assets in a portfolio and recalculates all metrics.

Args: name: The portfolio name. weights: New allocation weights per symbol. Must sum to 1.0.

Returns: Updated portfolio information with new metrics.

Example: result = update_portfolio_weights( name="tech_stocks", weights={"GOOG": 0.5, "AMZN": 0.3, "AAPL": 0.2} ) print(f"New Sharpe: {result['metrics']['sharpe_ratio']}")

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>",
      "weights": "<weights>"
    },
    "name": "update_portfolio_weights"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`weights`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.0.5Jan 26, 2026

TDQS

A3.9/5.0

Behavior3/5

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

No annotations exist, so description must cover behavioral traits. It mentions recalculation of metrics and a constraint (weights sum to 1.0), but does not disclose mutation permanence, required permissions, or side effects on other portfolio attributes.

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?

Well-structured with Args, Returns, and an example. The Returns line is generic but the example compensates. No superfluous text; each part serves a purpose.

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?

Given the tool's simplicity and presence of an output schema, the description covers the main purpose, parameters, constraint, and provides an example. However, it does not differentiate from related optimization tools, which would improve completeness.

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 description coverage is 0%, but the description explains both parameters: 'name: The portfolio name' and 'weights: New allocation weights per symbol. Must sum to 1.0.' This adds essential meaning, including the summation constraint, which is not in the schema.

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?

Clearly states 'Update the allocation weights of an existing portfolio' and explains that it changes weight distribution and recalculates metrics. This verb-resource pairing is specific and distinguishes it from creation or deletion tools.

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 implies usage for updating weights but does not specify when to use this tool versus alternatives like apply_optimization or optimize_portfolio. No explicit when-not or exclusion criteria are provided.

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