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Glama

ko-mcp

by io.github.SharpLu

get_institution_holdings

Get current stock holdings of an institutional investor (hedge fund, mutual fund, pension fund) from their latest SEC 13F filing. Returns top positions with share counts, values, and quarter-over-quarter changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number
limitNoResults per page
institutionYesInstitution CIK number (e.g. '1067983'), slug (e.g. 'berkshire-hathaway'), or name (e.g. 'Berkshire Hathaway') — names are resolved automatically.

Schema Changelog

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

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses the quarterly SEC filing source and that returns are 'top positions' with quarter-over-quarter changes. However, it does not mention pagination behavior (page/limit parameters) or error handling for unrecognized institutions. Adds some behavioral context but not comprehensive.

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?

Two sentences, no redundancy. First sentence states purpose and source, second sentence details output. Front-loaded with essential information, every word earns its place.

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?

For a tool with 3 parameters (1 required), no output schema, and no annotations, the description provides a solid overview. It explains the source, output, and institution resolution. It could mention pagination or the quarterly nature of data, but overall is sufficiently complete for effective use.

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?

Input schema covers 100% of parameters with descriptions. The description adds value by explaining the institution parameter accepts CIK, slug, or name (with automatic resolution), which the schema only mentions CIK and name. Also summarizes output fields (share counts, values, changes) providing context beyond 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?

The description clearly states the verb (get), resource (stock holdings of an institutional investor), and source (SEC 13F filing). It distinguishes from siblings like get_stock_holders (holder of a specific stock) and list_institutions (list of institutions) by focusing on holdings of a given institution.

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 specifies the data source (latest SEC 13F filing) and return content (top positions, share counts, values, changes). It implicitly suggests use for institutional holdings data, but does not explicitly exclude cases or mention alternatives. Adequate but lacking when-not-to-use guidance.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct resource and action, and descriptions explicitly disambiguate similar pairs (e.g., get_congress_member vs get_congress_trades, get_crypto_holder vs get_crypto_holders). No two tools appear to do the same thing.

Naming Consistency4/5

The dominant pattern is get_<noun>, with list_<noun> for enumerations. Minor deviations exist: a bare 'search' tool and the 'sec_' prefix on SEC filing tools break the uniform verb_noun style, but the pattern remains predictable.

Tool Count4/5

At 24 tools, this is on the heavier side, but the server spans multiple financial data domains (SEC filings, stocks, insider trading, crypto, rates, economics), so each tool has a clear purpose. It is just below the 'too many' threshold.

Completeness5/5

The tool surface is remarkably complete for financial data retrieval: SEC filing lifecycle is covered (list -> index -> document), institutional ownership is available from both stock and institution perspectives, and insider/congress/crypto/economic data are all present. No obvious gaps or dead ends.

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