Skip to main content
Glama
dacmail

indexa-capital-mcp-server

by dacmail

Get Indexa account performance

indexa_get_performance
Read-onlyIdempotent

Retrieve cumulative and annualized returns for your Indexa account over a custom date range. Optionally compare performance against benchmark or view forward projections.

Instructions

Retrieve the historical performance series for an Indexa account, with optional date filtering and projection data.

Performance values are returned in base 100 — a value of 105 at index N means +5% cumulative return since the start of the series. Per Indexa support, returns between two points are computed as: 100 * (return[end] / return[start] - 1).

Args:

  • account_number (string): Indexa account ID

  • date_from (string, optional): Filter the series to start on or after this date (YYYY-MM-DD)

  • date_to (string, optional): Filter the series to end on or before this date (YYYY-MM-DD)

  • include_projections (boolean, default false): Whether to include best/worst/expected forward projections in the JSON output. These can be large; leave off unless explicitly needed.

  • response_format ('markdown' | 'json'): Output format (default: 'markdown')

The Markdown format computes and displays:

  • Cumulative return over the period

  • Annualised return (estimated from the date range)

  • Plan expected return (Indexa's own projection)

  • Benchmark comparison and alpha (if benchmark series is present)

  • A sampled subset of the curve as a table (~8 points)

Returns: For JSON format, the structure is: { "plan_expected_return": number, // e.g. 0.0384 = +3.84%/year expected "performance": { "period": ["YYYY-MM-DD", ...], // dates "return": [number, ...], // base-100 actual return series "benchmark"?: [number, ...], // base-100 benchmark series "best"?: [number, ...], // best-case projection (if requested) "worst"?: [number, ...], // worst-case projection "expected"?: [number, ...] // expected projection } }

Examples:

  • Use when: "What's my YTD return on Indexa?" -> date_from = first day of year

  • Use when: "How has my account performed since I opened it?" -> no dates

  • Use when: "Compare my returns to the benchmark"

  • Don't use when: The user wants the current value (use indexa_get_portfolio) or transaction history (use indexa_get_transactions).

Error handling:

  • 404: account not found or no performance data yet (e.g. just opened).

  • 401/403: token invalid.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
account_numberYesIndexa account number (account_number field from indexa_get_me). Example: 'NK1NUTP1'.
date_fromNoLower bound for the returned series (YYYY-MM-DD). Omit for full history.
date_toNoUpper bound for the returned series (YYYY-MM-DD). Omit for latest available.
include_projectionsNoInclude best/worst/expected projection arrays in the JSON output. These can be very large; default false to keep responses small.
response_formatNoOutput format: 'markdown' for human-readable summary or 'json' for full structured data.markdown
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds important behavioral details beyond annotations: base-100 return interpretation, formula for returns between two points, and warning that projections can be large. No contradictions.

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?

Description is relatively long but well-structured with sections for purpose, args, returns, examples, and error handling. It is front-loaded with key info. Every sentence serves a purpose; no wasted words. Slightly verbose but necessary for a complex tool.

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

Completeness5/5

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

Despite no output schema, description provides detailed return format for both markdown and JSON, including field descriptions and types. Covers error codes and scenarios. For a 5-parameter tool with optional projections and output format choice, this is very thorough.

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 100%, so baseline is 3. Description adds significant value for each parameter: account_number references schema from another tool, dates specify YYYY-MM-DD, include_projections warns about size, response_format explains output differences. This goes beyond what schema provides.

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?

Description clearly states it retrieves historical performance series for an Indexa account, with specific verb 'Retrieve' and resource 'performance series'. It distinguishes from siblings by providing examples and explicitly warning not to use for current value (use indexa_get_portfolio) or transactions (use indexa_get_transactions).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use scenarios with examples like 'What's my YTD return?' and 'Don't use when' cases, offering specific alternative tools (indexa_get_portfolio, indexa_get_transactions). This gives clear guidance for the AI agent to choose the correct tool.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/dacmail/indexa-capital-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server