List top institutional investors (hedge funds, mutual funds, etc.) tracked in the SEC 13F database. Supports search by name and pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number | |
| limit | No | Results per page | |
| search | No | Search by institution name, CIK, or manager name (e.g. 'Klarman' -> Baupost) |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / search / descriptionPrevious value: -"Search by institution or founder name"New value: +"Search by institution name, CIK, or manager name (e.g. 'Klarman' -> Baupost)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It mentions search and pagination behavior and the data source, but does not define 'top', describe the return format, or address safety/rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core purpose, and no unnecessary words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with no output schema and no annotations, the description covers the essential purpose and capabilities, but lacks details on what 'top' means, ordering criteria, and the structure of returned institutions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema fully describes all three parameters (page, limit, search) with detailed descriptions and an example. The description only restates that search and pagination are supported, adding no new semantic meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists top institutional investors from the SEC 13F database, with specific examples (hedge funds, mutual funds). This distinguishes it from siblings like get_institution_holdings, which focus on individual holdings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context (SEC 13F database, search by name) and implies listing vs. getting details, but it does not explicitly mention when to use this tool over alternatives or any exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.