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US Economic, SEC EDGAR & On-Chain Data (x402)

SEC 13F Institutional Holdings

edgar_13f_holdings
Read-onlyIdempotent

Institutional stock holdings for a fund manager, from its latest SEC Form 13F.

13F filings split the actual holdings into a separate "information table" XML document that the filing index does not point at directly; this locates it, parses every position, and rolls up lots reported separately (different share classes, put/call splits) into one row per issuer.

When to use: seeing what a fund or institution holds and how much, tracking "smart money" positioning, portfolio research.

When NOT to use: real-time positions (13F is filed up to 45 days after quarter end, so this is always historical), short positions (13F does not require disclosing shorts), or non-U.S. filers.

Args:

  • ticker (string, required): the FILER's ticker (if it has one) or its SEC CIK, e.g. "1067983" for Berkshire Hathaway.

  • limit (integer, optional, default 25): maximum holdings to return, largest by value first (1-200).

Returns structuredContent: { "cik": "0001067983", "filer": "BERKSHIRE HATHAWAY INC", "periodOfReport": "2026-06-30", "filedAt": "2026-08-14", "totalPositions": 45, "totalValueUsd": 293000000000, "holdings": [ { "issuer": "ALLY FINL INC", "cusip": "02005N100", "valueUsd": 900335661000, "shares": 19593812, "lots": 3 } ], "source": "https://www.sec.gov/edgar" }

Reports the most recently FILED 13F-HR. Values are whole USD, taken directly from the filing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum holdings to return, largest first. Default 25.
tickerYesThe FILER's ticker or SEC CIK, e.g. "1067983" for Berkshire Hathaway.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description goes far beyond this by disclosing the 13F information table XML discovery, rollup of lots/share classes/put-call splits, the 'most recently filed' semantics, and the historical lag. It also explicitly notes that values are taken directly from the filing. This rich behavioral detail helps the agent understand exactly what happens under the hood.

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 moderately long but every block earns its place: purpose, technical complication (XML table), use cases, exclusions, args, and a full structuredContent example. It is well-organized with headers and front-loaded with the core purpose. No redundant or filler sentences.

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?

With no output schema, the description compensates fully by providing a complete structuredContent example with field names, types, and sample values. It also covers prerequisites (ticker or CIK), constraints (limit range, historical data), and the source URL. For a tool of this complexity, the description is fully self-contained and leaves no critical gap.

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?

Schema description coverage is 100%: both 'ticker' and 'limit' are fully described in the schema, including default and range for limit. The description largely repeats this information (e.g., 'ticker (string, required): the FILER's ticker or its SEC CIK') without adding new meaning beyond the schema. Baseline 3 is appropriate since the schema carries the semantic burden adequately.

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?

The description opens with a specific verb+resource: 'Institutional stock holdings for a fund manager, from its latest SEC Form 13F.' It clearly distinguishes this tool from siblings by explaining scope (latest 13F), what it returns (holdings with values, shares, lots), and explicit non-use cases (real-time, shorts, non-U.S. filers). This makes the tool's purpose unmistakable.

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?

The description provides explicit 'When to use' (fund holdings, smart money tracking, portfolio research) and 'When NOT to use' (real-time, shorts, non-U.S. filers) with reasoning (45-day filing lag, no short disclosure). However, it does not name any alternative sibling tools, stopping short of the full 'alternatives' criterion for a 5.

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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TDQS

A4.5/5.0
Disambiguation5/5

Every tool targets a distinct resource and action. The macro_* tools each cover one economic indicator, the edgar_* tools cover different SEC filing types, and the onchain_* tools are split by chain scope (single vs multi), asset type, and operation. Even the two data-cleaning tools are clearly distinct (JSON repair vs table parsing). No two tools appear to do the same thing.

Naming Consistency4/5

Names follow a mostly consistent snake_case pattern with domain prefixes: macro_*, edgar_*, onchain_*. The exceptions are bls_cpi (could be macro_cpi) and the utility tools structured_json_repair and tabular_to_json, which break the prefix pattern but are still descriptive and predictable. Overall, the convention is clear with minor deviations.

Tool Count3/5

21 tools is in the 'heavy' range (16-25). However, the server spans three distinct domains (US economic data, SEC EDGAR, on-chain data), and each tool serves a unique purpose within its domain. While it feels dense, the breadth is justified by the server's stated multi-domain scope.

Completeness4/5

The tool surface covers the major needs in each domain: key macro indicators, common EDGAR filings and searches, and core on-chain reads. Minor gaps exist (e.g., no PPI, no historical on-chain balances, no company CIK lookup), but agents can work around these with existing tools or by combining them.