ib-async-mcp

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get_account_summary

Retrieve account summary information from Interactive Brokers, including balances, positions, and performance metrics for portfolio management.

Instructions

Get account summary.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_account_summary"
  }
}

Input Schema

Name	Required	Description	Default
`account`	No	Account ID (optional)

Implementation Reference

src/ib_async_mcp/server.py:483-486 (handler)

The handler for the 'get_account_summary' tool, which fetches account summary data from the Interactive Brokers API.

if name == "get_account_summary":
    summary = ib.accountSummary(args.get("account", ""))
    return [{"account": v.account, "tag": v.tag, "value": v.value, "currency": v.currency} for v in summary]

src/ib_async_mcp/server.py:107-115 (registration)

The MCP tool registration for 'get_account_summary'.

    name="get_account_summary",
    description="Get account summary.",
    inputSchema={
        "type": "object",
        "properties": {
            "account": {"type": "string", "description": "Account ID (optional)"},
        },
    },
),

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Mar 25, 2026

TDQS

C2.5/5.0

Behavior2/5

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

No annotations exist, and the description does not disclose any behavioral traits such as side effects, authentication requirements, rate limits, or data freshness. The agent has no insight into the tool's behavior 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.

Conciseness3/5

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

The description is extremely short (two words), which is concise but comes at the cost of missing necessary context. It is not front-loaded with key decision factors, and it sacrifices clarity for brevity.

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?

Given the tool's optional parameter and lack of output schema, the description should explain what the account summary contains or how it relates to other tools. It fails to provide sufficient context for an agent to understand the tool's output.

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?

The input schema has 100% coverage for its one optional parameter, so the description adds no additional meaning. The baseline score of 3 applies because the schema already documents the parameter adequately.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Get account summary' indicates the tool retrieves a summary of an account, which is clear but vague. It distinguishes from siblings like get_accounts (list accounts) and get_account_values (get values) only by the term 'summary', but doesn't specify what the summary includes.

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 is provided on when to use this tool versus alternatives. There is no mention of prerequisites, preferred scenarios, or tool exclusions, leaving the agent without context for selection.

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