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MakAcp

SEC EDGAR MCP Server

by MakAcp

edgar_notes

Retrieve notes and disclosures from SEC filings to explain financial statement line items, including debt terms, revenue policies, lease schedules, and contingencies.

Instructions

Drill into the notes and disclosures behind financial statement numbers. Use this when you need to explain WHY a number is what it is — debt terms, revenue recognition policies, lease schedules, contingencies, etc.

Returns the note's narrative text, which statement line items it explains, and structured table data.

Examples:

  • What does Apple's debt note say? topic="debt", identifier="AAPL"

  • Revenue recognition policy: topic="revenue", identifier="MSFT"

  • All notes overview: identifier="TSLA" (no topic = table of contents)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
formNoFiling form type (default: 10-K). Use 10-Q for quarterly notes.10-K
topicNoNote topic to search for (e.g., 'debt', 'revenue', 'leases', 'contingencies'). Omit for table of contents.
detailNoDetail level: minimal (titles only), standard (context + tables), full (includes DataFrame data)standard
identifierYesCompany ticker (AAPL), CIK (320193), or name
Behavior4/5

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

Describes what the tool returns: narrative text, statement line items it explains, and structured table data. Also explains detail levels (minimal, standard, full). No annotations provided, so the description carries full burden; it adequately discloses behavior without contradictions.

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 short paragraphs plus bullet-style examples. Every sentence adds value, with the first sentence immediately stating purpose. No redundancy or unnecessary detail.

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?

Given the tool has 4 parameters, no output schema, and simple return structure, the description covers return types (narrative, tables) and detail levels. Missing are error cases and rate limits, but for a read-only document retrieval tool this is acceptable.

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 baseline is 3. The description adds value by providing examples of topic values (debt, revenue, leases) and clarifying that omitting topic gives a table of contents. This enriches the parameter meaning beyond the schema alone.

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 uses a specific verb 'drill into' and identifies the resource as 'notes and disclosures' behind financial statement numbers. It clearly distinguishes from sibling tools like edgar_read or edgar_filing by focusing on explanatory notes.

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?

Explicitly states when to use: 'when you need to explain WHY a number is what it is' with concrete examples (debt terms, revenue recognition). Does not explicitly state when not to use, but the context and examples imply it is for notes, not for raw filings or comparisons.

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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