SEC EDGAR filings for AI agents: company lookup, filings, financials, insider trades. No keys.
Resolve a stock ticker or company name to its SEC identity: CIK number, official name, ticker(s), exchange(s), industry (SIC), and fiscal year end. Start here before other Filings Intel calls.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Ticker (e.g. AAPL), company name, or CIK |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full disclosure burden and does well: it lists the concrete outputs (CIK, official name, tickers, exchanges, SIC, fiscal year end), making the tool's behavior predictable. It doesn't address failure modes or ambiguous matches, but for a simple lookup this is a solid disclosure.
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 with no filler: the first states the core action and outputs, the second gives workflow guidance. The most important scoping information is front-loaded, and 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 single-parameter lookup tool with no output schema, the description is nearly complete: it covers input types, output fields, and usage ordering. It could briefly mention that CIK is also accepted as input (as the schema does), but this is a minor gap given the schema is available.
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 already documents the single parameter fully (ticker, company name, or CIK) with an example, so schema coverage is 100%. The description adds the context of resolving to SEC identity but doesn't add parameter-level detail 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 uses a specific verb ('resolve') with a precise resource ('stock ticker or company name' → 'SEC identity') and enumerates the exact output fields. This clearly distinguishes it from sibling tools like filing_search or financials, which focus on retrieving filings or data rather than identity resolution.
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 instruction 'Start here before other Filings Intel calls' is an explicit usage directive that tells the agent to use this tool first in a workflow. It does not name specific sibling alternatives or spell out when not to use each, so it falls just short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Full-text search across all EDGAR filings for a keyword or phrase (e.g. a risk factor, product name, or executive). Returns matching filings with company, form type, and date. Optionally restrict to a form type.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. | |
| query | Yes | Search phrase | |
| form_type | No | Optional form filter, e.g. 8-K |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention that this is a full-text search and what fields are returned, which is helpful. But it remains silent on result ordering, pagination, rate limits, whether the search covers the full document text versus metadata, or what happens when no matches are found. The disclosure is adequate but not rich.
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 with no filler. The main verb, resource, and output are front-loaded, and the optional filter is mentioned at the end as a natural extension. Every sentence 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 three-parameter search tool, the description covers the core invocation needs: what to search, what is returned, and how to narrow by form type. There is no output schema, so the return-value hint (company, form type, date) is valuable. It is not fully complete because it omits behavior like result limits or ordering, but for this low complexity it is close to sufficient.
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?
Schema description coverage is 100%, so the baseline is 3. The description adds small semantic value by giving example query types ('risk factor, product name, or executive') and clarifying that form_type is an optional filter. However, it does not add new meaning for the limit parameter, so the overall lift over the schema is minor.
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 opens with a specific verb and resource: 'Full-text search across all EDGAR filings for a keyword or phrase.' It also clarifies the output (matching filings with company, form type, and date), which distinguishes it from sibling tools like company_lookup or recent_filings without needing to open their schemas.
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 clearly implies the intended use case: searching filing content for a keyword or phrase. It also notes the optional form-type restriction, giving the reader a sense of how to narrow scope. However, it never explicitly contrasts with sibling tools (e.g., 'use recent_filings to list filings without a keyword'), so it stops short of full when-to-use versus 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.
Get reported financial facts for a company from XBRL data in its filings: revenue, net income, total assets, liabilities, equity, EPS, and cash — most recent reported values, or the full history of one specific us-gaap concept.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Ticker, name, or CIK | |
| concept | No | Optional specific us-gaap concept, e.g. Revenues, NetIncomeLoss, Assets |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral disclosure burden. It does reveal an important behavioral distinction: omitting 'concept' returns most recent reported values, while supplying a us-gaap concept returns the full history of that concept. It also grounds the data source as XBRL-reported filings, which is meaningful context beyond the tool name.
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?
The description is a single, information-dense sentence with no filler. It front-loads the core action and resource, lists the relevant metrics, and then adds the key mode distinction in a compact em-dash clause. Every part contributes to correct tool selection.
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 two-parameter tool with no nested objects and no output schema, the description is largely complete: it identifies inputs, data source, covered metrics, and output modes. It could further clarify whether 'most recent' refers to latest quarterly or annual reporting period, but overall an agent has enough information to invoke it correctly.
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 already documents both parameters at 100% coverage, providing a baseline of 3. The description adds value by explaining that the presence or absence of 'concept' changes the output mode from most-recent snapshot to full history, and by giving concrete examples of what concepts map to. This is more than the schema alone provides.
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 states a specific verb ('Get') and resource (reported financial facts from XBRL filings), and enumerates the exact data items available. It clearly distinguishes itself from siblings like filing_search or company_lookup by focusing on financial statement facts rather than filing discovery or entity metadata.
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 implies when to use the tool: when you need revenue, net income, assets, liabilities, equity, EPS, or cash from XBRL filings. It does not explicitly state when not to use it or name alternatives from the sibling list, so an agent must infer the appropriate usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List recent insider ownership filings (Form 3/4/5) for a company — the filings officers, directors, and 10% owners submit when they buy or sell shares. Returns the filings with dates and links.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. | |
| query | Yes | Ticker, name, or CIK |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It does convey that this is a listing operation, that results are 'recent,' and that output includes dates and links. However, it does not mention ordering, pagination, possible data delays, or how 'recent' is defined, which leaves some ambiguity for a tool with no annotation safety profile.
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 tightly written sentences with no filler. The main action and resource are front-loaded, and the explanatory clause about who files these forms is useful context rather than redundancy.
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 two-parameter list tool without an output schema, the description provides enough to select and invoke it: it defines the data type, scope, and return contents. It could be more complete by noting default limit behavior or clarifying 'recent,' but these are minor for this complexity level.
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?
Schema description coverage is 100%, so both parameters are already documented. The description adds only a light semantic cue that the query refers to 'a company,' reinforcing the schema's 'Ticker, name, or CIK.' This meets the baseline but adds little 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 names a specific verb ('List'), a precise resource ('insider ownership filings (Form 3/4/5)'), and clarifies the actor (officers, directors, 10% owners). This distinguishes it from sibling tools like recent_filings or filing_search, which cover broader filing categories.
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 purpose strongly implies when to use it: whenever insider ownership/transaction filings are needed. However, it never explicitly contrasts with alternatives such as filing_search or recent_filings, nor states when not to use this tool. The usage guidance is implied rather than stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List a company's most recent SEC filings (10-K annual reports, 10-Q quarterly, 8-K material events, S-1 IPO registrations, etc.) with filing dates and direct document links. Optionally filter by form type.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return. | |
| query | Yes | Ticker, name, or CIK | |
| form_type | No | Optional filter, e.g. 10-K, 10-Q, 8-K, 4 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the behavioral burden. It discloses the key output fields (filing dates and direct document links) and optional form-type filtering, but it does not mention ordering guarantees, pagination/limit behavior, or what happens when no filings are found. This is adequate for a simple read-only list tool 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and resource, then adds output specifics and the optional filter. There is no redundancy or filler.
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?
Given the low complexity, full schema coverage, and read-only nature, the description is mostly complete: it states what the tool lists, what fields are returned, and the optional filter. It stops short of fully complete because it does not address ordering details or the relationship to filing_search, but these are minor for a simple listing tool.
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?
Schema description coverage is 100%, so query, limit, and form_type are already documented. The description adds examples of form types (10-K, 10-Q, 8-K, S-1) but does not add meaningfully beyond the schema for the parameters themselves.
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 uses a specific verb and resource: 'List a company's most recent SEC filings' with concrete output details (filing dates, direct document links). It is clear and unambiguous, but it does not explicitly differentiate itself from the sibling filing_search tool.
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 implies usage for retrieving recent company filings and mentions optional form-type filtering, but it gives no explicit guidance on when to prefer this tool over filing_search or when not to use it. No alternatives or exclusions are stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
company_lookupfiling_searchfinancialsinsider_transactionsrecent_filingsClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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SEC EDGAR filings for AI agents: company lookup, filings, financials, insider trades. No keys.
SEC EDGAR financials, insider trading, and economic data for AI agents. US GAAP + IFRS.
SEC EDGAR fundamentals as agent tools: look up or screen US public companies. Free, no key, CC0.
Normalized SEC EDGAR data for AI agents: XBRL financials, 10-K risk diffs, Form 4 insider trades.
Add one secure layer between your agents and this server.
Each tool maps to a clearly distinct SEC data need: company identity resolution, full-text filing search, XBRL financials, insider transaction filings, and recent filing lists. Even the two filing-related tools are sharply separated by global keyword search versus company-specific recent activity.
All names use lowercase snake_case, but the pattern is mixed: company_lookup and filing_search use object+action, while financials, insider_transactions, and recent_filings are noun phrases. The names are readable and descriptive, but there is no consistent verb_noun structure across the set.
Five tools is well-scoped for an SEC filings intelligence server, covering lookup, search, financials, insider activity, and recent filings without redundant surface. Each tool has a clear role and the count sits comfortably in the ideal range.
The main research workflow is covered: identify a company, search filings, pull financial facts, inspect insider filings, and list recent SEC submissions. Minor gaps exist, such as no direct tool for fetching a single filing's full text or parsed insider transaction details, but returned links and financial data cover most needs.
