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FinBridge

by kr.gronox.mcp

Get Insider Trades (SEC Form 4)

get_edgar_insider_trades
Read-only

Latest insider transactions for a US company, parsed from SEC Form 4 filings, with a buy-vs-sell summary and an optional buy/sell filter. Each trade lists the reporting insider, their relationship, and non-derivative (common stock) transactions.

Insider BUYS (open-market purchases, code P) are a stronger sentiment signal than sells (code S), which happen for many reasons (diversification, taxes). Use tx_type to monitor one side.

Args:

  • company (required): ticker / company name / CIK

  • limit: number of most-recent Form 4 filings to parse, 1-25 (default 10)

  • tx_type: 'all' (default) | 'buy' (code P purchases only) | 'sell' (code S sales only)

Returns: {company:{cik, name, ticker}, tx_type, summary:{buys:{count,shares,value}, sells:{count,shares,value}}, count, trades:[{filedAt, owner, relationship, url, transactions:[{date, code, shares, price_per_share, acquired_or_disposed, shares_owned_after}]}], notes}. summary totals cover the whole fetched window regardless of the filter; value = shares x price where a price is reported. Transaction codes: P=open-market purchase, S=open-market sale, M=option exercise, F=shares withheld for tax, A=award/grant, G=gift. acquired_or_disposed: A=acquired, D=disposed.

Examples:

  • "insider BUYING at Apple" -> {company:'AAPL', tx_type:'buy'}

  • "recent insider SELLING at Nvidia" -> {company:'NVDA', tx_type:'sell'}

  • "all TSLA insider activity, more history" -> {company:'TSLA', limit:25}

Use when: monitoring insider buy/sell activity (officers, directors, 10% owners) for a US-listed company. Larger 'limit' widens the time window. Don't use for: institutional holdings (use get_edgar_13f), Korean companies, or derivative-only detail (option grids are skipped).

Errors: unknown company -> use search_edgar_company; a filter with no matching transactions returns count 0 (not an error); unparseable Form 4 XMLs are skipped and counted in notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of most-recent Form 4 filings to parse (default 10)
companyYesUS company: ticker (e.g. 'AAPL', 'BRK-B' or 'BRK.B'), company name, or CIK number
tx_typeNo'all' (default), 'buy' = open-market purchases (code P) only, 'sell' = sales (code S) onlyall

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
notesNo
tradesYes
companyYes
summaryNo
tx_typeNo

Schema Changelog

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

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses important behavioral details: summary totals cover the full window regardless of filter, value is calculated as shares x price, unparseable XMLs are skipped and counted in notes, and empty filtered results return count 0 rather than error. This is rich, non-obvious behavior that agents need.

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 long but every section earns its place: purpose, args, return shape, transaction codes, examples, use/don't-use, and error behavior. The structure is front-loaded with the core purpose and uses compact labeled sections for quick scanning.

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?

For a complex SEC-filings tool with three parameters, an output schema, and multiple sibling tools, the description covers all critical contexts: company identification formats, filtering semantics, edge cases, error handling, and exclusions. Nothing essential is left for the agent to infer.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real value: it explains the meaning of transaction codes (P, S, M, F, A, G), clarifies that summary aggregates span the whole window despite tx_type filtering, and provides example inputs like 'AAPL' and 'NVDA'. This goes beyond the schema's field-level descriptions.

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 and resource: 'Latest insider transactions for a US company, parsed from SEC Form 4 filings' plus a buy-vs-sell summary and filter. It clearly identifies the SEC Form 4 domain, distinguishes itself from DART-based insider trades, and explicitly says 'Don't use for: ... Korean companies'.

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?

The description provides explicit when-to-use ('monitoring insider buy/sell activity... for a US-listed company') and when-not-to-use guidance, naming the sibling alternative 'get_edgar_13f' for institutional holdings. It also gives concrete query examples mapping natural language to parameters.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct resource+action targets, and the overlapping screen_* tools are thoroughly cross-referenced with 'use screen_X instead' guidance. Minor ambiguity exists between get_disclosure_feed, get_dart_filings, and get_dart_major_events, which all surface KR filings from different angles but remain distinguishable.

Naming Consistency5/5

Every tool follows a consistent verb_noun snake_case pattern: get_* for retrievers, screen_* for screeners, search_* for lookups, plus action verbs like analyze_, backtest_, compare_, import_, and query_. Subfamilies (dart_*, edgar_*, fred_*, crypto_*) are consistently prefixed, making tool selection predictable.

Tool Count3/5

37 tools is heavy, and the four momentum screeners (canslim/kell/minervini/schwartz) plus three KR disclosure tools could arguably be collapsed into parameterized variants. However, the server's unusually broad scope—KR/US/TW/JP/EU equities, crypto, macro, portfolio, backtesting—means most tools earn their place, so the count is high but not chaotic.

Completeness4/5

The surface covers the core workflow well: search, prices, fundamentals, filings, insider trades, valuation, screeners, backtesting, and portfolio tracking for KR/US, plus crypto and macro. Notable gaps are the lack of single-company financial-statement tools for TW/JP/EU (only available through screen_companies) and no real-time stock quotes, but these are workable for the stated local-database research purpose.

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