# io.github.CloudCorpRecords/filinglens (npm · @reneturcios/filinglens)

SEC-filed company financials with citations, plus market data and technical indicators.

- Trust score: 68/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- npm · `@reneturcios/filinglens`: 68/100 (this document), [markdown](https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens.md), [page](https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens)
- oci · `ghcr.io/cloudcorprecords/filinglens`: 38/100, [markdown](https://verifymcp.io/servers/cloudcorprecords-filinglens/ghcr-io-cloudcorprecords-filinglens.md), [page](https://verifymcp.io/servers/cloudcorprecords-filinglens/ghcr-io-cloudcorprecords-filinglens)

## Channel facts

- Registry: `npm`
- Package: `@reneturcios/filinglens`
- Version: `0.1.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-05.

- **Supply Chain Security**: 98/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - 30 of 92 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 0 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 61/100
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 3569 tokens (~169/item across 21 items; 21 tools + 0 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 3/100
  - Stability observed for 1 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 21 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 21 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the io.github.CloudCorpRecords/filinglens MCP server?

io.github.CloudCorpRecords/filinglens runs locally as an npm package, launched with npx -y @reneturcios/filinglens. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add cloudcorprecords-filinglens -- npx -y @reneturcios/filinglens
```

### Cursor

```json
{
  "mcpServers": {
    "cloudcorprecords-filinglens": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/filinglens"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "cloudcorprecords-filinglens": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/filinglens"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add cloudcorprecords-filinglens -- npx -y @reneturcios/filinglens
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "cloudcorprecords-filinglens": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@reneturcios/filinglens"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add cloudcorprecords-filinglens --command npx --arg -y --arg @reneturcios/filinglens
```

### Hermes

```yaml
mcp_servers:
  cloudcorprecords-filinglens:
    command: "npx"
    args: ["-y", "@reneturcios/filinglens"]
```

### Netclaw

```json
{
  "McpServers": {
    "cloudcorprecords-filinglens": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "@reneturcios/filinglens"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add cloudcorprecords-filinglens -t stdio -c npx -a -y @reneturcios/filinglens
```

### Other

```json
{
  "mcpServers": {
    "cloudcorprecords-filinglens": {
      "command": "npx",
      "args": [
        "-y",
        "@reneturcios/filinglens"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-05 (score 68, +1)

No change was recorded against any check on this day. Stability & Change Management went from 0 to 3. That category is still filling its 30-day observation window: 0 days of observed history at the previous scan, 1 at this one. The score rises as the window fills, whether or not the server changes.

### 2026-11-04 (score 67)

First indexed and scored.

## MCP tools (21)

### `fetch_time_series_daily` (~149 tokens)

[Personal research only] Fetch daily stock data with OHLCV (Open, High, Low, Close, Volume) information for each trading day.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (inclusive).
- `max_data_points` (integer): Maximum number of time series data points to return.
- `outputsize` (string): Data output size.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (inclusive).
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to retrieve daily data

### `fetch_time_series_weekly` (~137 tokens)

[Personal research only] Fetch weekly stock data with OHLCV (Open, High, Low, Close, Volume) aggregated by week.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (inclusive).
- `max_data_points` (integer): Maximum number of time series data points to return.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (inclusive).
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to retrieve weekly data

### `fetch_time_series_monthly` (~137 tokens)

[Personal research only] Fetch monthly stock data with OHLCV (Open, High, Low, Close, Volume) aggregated by month.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (inclusive).
- `max_data_points` (integer): Maximum number of time series data points to return.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (inclusive).
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to retrieve monthly data

### `search_endpoint` (~64 tokens)

[Personal research only] Searches for stock symbols and company names based on keywords (e.g., 'Tesla', 'Microsoft Corp').

Input parameters:

- `keywords` (string, required): Keywords to search for company names or stock symbols (e.g., 'Tesla', 'Microsoft Corp', 'AAPL')

### `fetch_quote` (~62 tokens)

[Personal research only] Fetches the latest price and trading information for a stock ticker symbol.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to fetch the latest price and trading…

### `fetch_news_sentiment` (~164 tokens)

[Personal research only] Fetch news sentiment analysis data with sentiment scores, relevance scores, and article metadata.

Input parameters:

- `datatype` (string): Response data type.
- `limit` (integer): Maximum number of news articles to return (1-200).
- `sort` (string): Sort order for results.
- `tickers` (string, required): Comma-separated list of ticker symbols to filter news articles.
- `time_from` (string): Start time for news articles in YYYYMMDDTHHMM format (e.g., '20240101T0000')
- `time_to` (string): End time for news articles in YYYYMMDDTHHMM format (e.g., '20240131T2359')
- `topics` (string): Optional news topics filter.

### `fetch_company_overview` (~70 tokens)

[Personal research only] Fetch comprehensive company overview including business description, financial ratios, market capitalization, dividend information, and key financial metrics.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to retrieve comprehensive company over…

### `fetch_income_statement` (~73 tokens)

[Personal research only] Fetch annual and quarterly income statement data including revenue, expenses, net income, EPS, and other profit & loss metrics.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'GOOGL') for which to retrieve annual and quarterly inco…

### `fetch_balance_sheet` (~71 tokens)

[Personal research only] Fetch annual and quarterly balance sheet data including assets, liabilities, shareholders' equity, and other financial position metrics.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'GOOGL') for which to retrieve annual and quarterly bala…

### `fetch_cash_flow` (~67 tokens)

[Personal research only] Fetch annual and quarterly cash flow statement data including operating, investing, and financing cash flows.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'GOOGL') for which to retrieve annual and quarterly cash…

### `fetch_earnings` (~77 tokens)

[Personal research only] Fetch annual and quarterly earnings data including EPS (earnings per share) estimates vs actual results, surprise percentages, and earnings growth trends.

Input parameters:

- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'GOOGL') for which to retrieve annual and quarterly earn…

### `fetch_exchange_rate` (~86 tokens)

[Personal research only] Fetch real-time currency exchange rates between two currencies with bid/ask prices and conversion rates.

Input parameters:

- `from_currency` (string, required): Source currency code (e.g., 'USD', 'EUR', 'GBP') to convert from
- `to_currency` (string, required): Target currency code (e.g., 'USD', 'EUR', 'JPY') to convert to

### `fetch_sma` (~203 tokens)

[Personal research only] Fetch Simple Moving Average (SMA) technical indicator time series with customizable time periods.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (e.g., '2024-12-31').
- `interval` (string, required): Time interval for data points.
- `max_data_points` (integer): Maximum number of time series data points to return.
- `series_type` (string): Price data to use for calculation.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (e.g., '2024-01-01').
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to calculate Simple Moving Average
- `time_period` (integer, required): Number of data points to use for moving average calculation (e.g., 20 for 20-day SMA)

### `fetch_ema` (~206 tokens)

[Personal research only] Fetch Exponential Moving Average (EMA) technical indicator time series with greater weight on recent prices.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (e.g., '2024-12-31').
- `interval` (string, required): Time interval for data points.
- `max_data_points` (integer): Maximum number of time series data points to return.
- `series_type` (string): Price data to use for calculation.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (e.g., '2024-01-01').
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to calculate Exponential Moving Average
- `time_period` (integer, required): Number of data points to use for moving average calculation (e.g., 12 for 12-period EMA)

### `fetch_macd` (~238 tokens)

[Personal research only] Fetch MACD (Moving Average Convergence Divergence) technical indicator time series with signal line and histogram.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (e.g., '2024-12-31').
- `fastperiod` (integer): Fast EMA period for MACD calculation (default: 12)
- `interval` (string, required): Time interval for data points.
- `max_data_points` (integer): Maximum number of time series data points to return.
- `series_type` (string): Price data to use for calculation.
- `signalperiod` (integer): Signal line EMA period for MACD calculation (default: 9)
- `slowperiod` (integer): Slow EMA period for MACD calculation (default: 26)
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (e.g., '2024-01-01').
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to calculate MACD

### `fetch_rsi` (~192 tokens)

[Personal research only] Fetch RSI (Relative Strength Index) momentum oscillator time series ranging from 0 to 100.

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (e.g., '2024-12-31').
- `interval` (string, required): Time interval for data points.
- `max_data_points` (integer): Maximum number of time series data points to return.
- `series_type` (string): Price data to use for calculation.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (e.g., '2024-01-01').
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to calculate RSI
- `time_period` (integer): Number of periods for RSI calculation (typically 14)

### `fetch_bbands` (~238 tokens)

[Personal research only] Fetch Bollinger Bands technical indicator time series with upper band, lower band, and middle line (SMA).

Input parameters:

- `datatype` (string): Response data type.
- `end_date` (string): Optional end date filter in YYYY-MM-DD format (e.g., '2024-12-31').
- `interval` (string, required): Time interval for data points.
- `max_data_points` (integer): Maximum number of time series data points to return.
- `nbdevdn` (integer): Number of standard deviations for lower band (typically 2)
- `nbdevup` (integer): Number of standard deviations for upper band (typically 2)
- `series_type` (string): Price data to use for calculation.
- `start_date` (string): Optional start date filter in YYYY-MM-DD format (e.g., '2024-01-01').
- `symbol` (string, required): Stock ticker symbol (e.g., 'AAPL', 'MSFT', 'TSLA') for which to calculate Bollinger Bands
- `time_period` (integer): Number of periods for moving average calculation (typically 20)

### `analyze_stock` (~387 tokens)

[Personal research only] One-call stock brief. `filed` holds fundamentals from SEC filings (TTM revenue and growth, gross and
operating margin, net income, free cash flow, net debt; for banks net revenue, net interest income,
efficiency ratio, PPNR, provisions, loans, deposits, ROE, ROTCE and tangible book; for broker-dealers
efficiency ratio, pretax margin, compensation ratio and ROE; for insurers total revenues, premiums earned,
net investment income, benefits and losses, a simple combined ratio for P&C insurers, ROE, and book value
per share with and without AOCI), each filing cited by accession in
sources.edgar (https://www.sec.gov/Archives/edgar/data/{cik}/{accession without dashes}/). A balance
input the newest filing omits comes from the latest filing within 15 months, dated in inputs_as_of.
\`market` holds delayed price, 52-week range, 50/200-day averages and RSI(14); `derived` holds market
cap, P/E (on filed diluted EPS LTM), P/B and P/TBV (insurers: P/B and P/B ex-AOCI), each with its inputs. A figure that couldn't be
computed is in gaps with its reason; lines that don't apply to the company's layout are left out (layout_note). Up to 4 descriptive
observations, including any quarter whose tax rate or non-operating income moves net income. News
sentiment on Pro. Start here for "tell me about X".

Personal research only: on every plan, this tool's output is for your own personal, non-commercial research. Do not use it in a commercial product, client deliverable or service.

Input parameters:

- `symbol` (string, required): Stock ticker, e.g. 'AAPL'

### `compare_stocks` (~238 tokens)

[Personal research only] Side-by-side comparison of 2-6 stocks as one table: TTM revenue and growth, pretax margin, net income
growth and diluted EPS growth from SEC filings (each row's window ends on its ttm_to), net debt for
standard layouts, delayed price, day change, distance from the 52-week high and trend, market cap, and
P/E on filed diluted EPS LTM (FY + YTD - prior YTD). `order` lists each filed figure highest first, P/E
lowest first. `comparability` says what revenue means per layout; cell_notes say what moves a figure.
Filings are cited by accession in sources.edgar: open
https://www.sec.gov/Archives/edgar/data/{cik}/{accession without dashes}/.

Personal research only: on every plan, this tool's output is for your own personal, non-commercial research. Do not use it in a commercial product, client deliverable or service.

Input parameters:

- `symbols` (array, required): 2 to 6 tickers, e.g. ['NVDA', 'AMD']

### `get_fact` (~288 tokens)

One reported figure from SEC filings, with its citation: filing accession number, form, filing
date, XBRL tag, period and a link to the filing. Restated values are listed. A figure the company
never reported comes back as missing, never estimated. Values are in units as filed (USD, shares,
USD/shares). A value and its as_originally_reported version come only from financial statements
(10-K, 10-Q, their amendments and transition reports, 20-F, 40-F), never a proxy or an 8-K.

Input parameters:

- `as_of`: Optional date: return the figure as it was on file then (before any later restatement)
- `company` (string, required): Ticker (e.g. 'AAPL') or SEC CIK
- `concept` (string, required): Line item such as 'revenue', 'net_income', 'eps_diluted', 'total_assets', 'operating_cash_flow', 'shares_outstanding', 'book_value_per_share', 'net_debt', 'dividend_payout_ratio', 'net_revenues', or…
- `period` (string): 'latest', a fiscal year 'FY2025', a fiscal quarter 'FY2025 Q2', or a period end date '2025-06-28'

### `financials` (~422 tokens)

A financial statement from SEC filings, newest period first, every value traceable to its filing.
Quarterly figures the company reported only year-to-date are derived (e.g. Q4 = FY - 9M) and marked;
per-share values and share counts can't be derived that way and are null with reason not_derivable.
A line the company tagged with its own element is null with reason custom_element. Common equity and the
book values from it are null with reason pending when a preferred issue or redemption follows the last
tagged liquidation preference.
Every null carries a reason, in cell_notes or (when all of a row's nulls share it) on the row. Banks,
insurers and broker-dealers get not_applicable, with a reason, for lines they don't present (capex,
current assets, total debt for banks and brokers); banks get loans, allowance and deposits. Broker-dealers
and asset managers get the bank layout under net_revenues, with compensation and the compensation ratio.
Balance sheets include common equity, book value per share and net debt. A balance the period's own
filing didn't present is null, with any later comparative value in a note. A derived or fallback line equal to
another row in every column (total equity with no NCI) is named in same_as instead of shown, and a derived Q4
with the opposite sign to Q1-Q3 says so. Values are in units as filed. Values and earlier
versions come only from financial statements (10-K, 10-Q, their amendments and transition reports,
20-F, 40-F).

Input parameters:

- `as_of`: Optional date: the statement as it was on file then
- `company` (string, required): Ticker (e.g. 'AAPL') or SEC CIK
- `limit` (integer): Number of periods, 1 to 8
- `period_type` (string): 'annual' or 'quarterly'
- `statement` (string): 'income', 'balance' or 'cashflow'

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens#diagnostics

## Score history

- 2026-11-05: 68
- 2026-11-04: 67

## Common questions

### What is the io.github.CloudCorpRecords/filinglens MCP server?

io.github.CloudCorpRecords/filinglens is an MCP server listed in the public MCP registry as io.github.CloudCorpRecords/filinglens. SEC-filed company financials with citations, plus market data and technical indicators. This page covers its npm package (@reneturcios/filinglens).

### Is the io.github.CloudCorpRecords/filinglens MCP server safe to use?

io.github.CloudCorpRecords/filinglens scores 68 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. It declares no install or post-install scripts. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the io.github.CloudCorpRecords/filinglens MCP server expose?

io.github.CloudCorpRecords/filinglens exposes 21 tools: fetch_time_series_daily, fetch_time_series_weekly, fetch_time_series_monthly, search_endpoint, fetch_quote, and 16 more. Their descriptions and schemas cost roughly 3,569 tokens of context every time the server is loaded.

### Is the io.github.CloudCorpRecords/filinglens MCP server still maintained?

io.github.CloudCorpRecords/filinglens is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the io.github.CloudCorpRecords/filinglens MCP server under?

io.github.CloudCorpRecords/filinglens declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- npm package: https://www.npmjs.com/package/@reneturcios/filinglens
- Socket report: https://socket.dev/npm/package/@reneturcios/filinglens
- Repository: https://github.com/CloudCorpRecords/filinglens
- Changelog RSS feed: https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens.xml
- Changelog JSON feed: https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens.json
- HTML version of this page: https://verifymcp.io/servers/cloudcorprecords-filinglens/reneturcios-filinglens