Datavidence Financials
PYPI · DATAVIDENCE-FINANCIALS · SCANNED SEP 21
Normalized US-GAAP financial statements & fundamentals from SEC EDGAR, as MCP tools for LLM agents.
Available components
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. How we score → Why this is hard to score →
Supply Chain Security100
- No malware found by supply-chain analysis.Pass
- No known CVEs affecting this package version or its production dependencies.Pass
- Runs setuptools.build_meta at install time, a recognised native-build step with no shell scripting around it. View diagnostics → Pass
- 1 of 32 dependencies flagged as unhealthy. View diagnostics → Partial
Provenance & Transparency48
- Source repository is publicly reachable at the declared URL. View diagnostics → Pass
- Provenance check failed: no build-provenance attestation is published. See how to fix → View diagnostics → Fail
- Clear OSI-approved license (MIT).Pass
- Actively maintained (last published 3 days ago).Pass
- Publishes a security disclosure policy (SECURITY.md).Pass
Schema Quality & AI Usability65
- AI-judged instruction clarity (good).Pass
- Context-footprint check failed: tool/resource definitions use about 676 tokens (~169/item across 4 items; 4 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management0
- Stability not yet verified: not enough scan history yet (needs a 30-day window).Unverified
Tool Coverage67
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 0% of tool parameters carry a description.Fail
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 4 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 5 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities100
- Implements a current MCP spec version (2026-07-28).Pass
Unverified: 1 category
A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.
How do I install the Datavidence Financials MCP server?
Datavidence Financials runs locally as a PyPI package, launched with uvx datavidence-financials. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
pypi · datavidence-financials
claude mcp add ai-datavidence-datavidence-financials -- uvx datavidence-financials
{
"mcpServers": {
"ai-datavidence-datavidence-financials": {
"command": "uvx",
"args": [
"datavidence-financials"
]
}
}
} {
"servers": {
"ai-datavidence-datavidence-financials": {
"command": "uvx",
"args": [
"datavidence-financials"
]
}
}
} codex mcp add ai-datavidence-datavidence-financials -- uvx datavidence-financials
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"ai-datavidence-datavidence-financials": {
"type": "local",
"command": [
"uvx",
"datavidence-financials"
],
"enabled": true
}
}
} openclaw mcp add ai-datavidence-datavidence-financials --command uvx --arg datavidence-financials
mcp_servers:
ai-datavidence-datavidence-financials:
command: "uvx"
args: ["datavidence-financials"] {
"McpServers": {
"ai-datavidence-datavidence-financials": {
"Transport": "stdio",
"Command": "uvx",
"Arguments": [
"datavidence-financials"
]
}
}
} assistant mcp add ai-datavidence-datavidence-financials -t stdio -c uvx -a datavidence-financials
{
"mcpServers": {
"ai-datavidence-datavidence-financials": {
"command": "uvx",
"args": [
"datavidence-financials"
]
}
}
} Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 17 Sept 26 67
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 21 Sept 2026 · Analysed pypi/datavidence-financials@0.1.2
Provenance No attestation
The registry publishes no build provenance for this version, so there is nothing to verify.
| Result | No attestation |
|---|---|
| Ecosystem | pypi |
Background: How many MCP packages publish verified provenance →
Install scripts 1 script
| Hook | Tier | Command |
|---|---|---|
| build_backend | allowlisted | setuptools.build_meta |
Background: Why install scripts are a supply-chain risk →
Dependencies 32 packages
| Packages resolved | 32 |
|---|---|
| No linked repository | 1 |
| Tree resolution | Complete |
Background: SBOMs and build attestations, explained →
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
get_financials ~198
Retrieve normalized US-GAAP financial statements (income statement, balance sheet, cash flow) for one company and fiscal year, from SEC EDGAR XBRL. Identify the company by `ticker` OR `cik`. Use `as_of` (ISO YYYY-MM-DD) to get the figures as originally reported on that date — no look-ahead bias — for backtests. Set `include_provenance=true` to attach, for every value, the SEC accession, filed date, and a direct EDGAR source URL for citation. Set `include_ratios=true` for margins, ROA/ROE, and leverage derived from the same statements. Returns the normalized data object.
| Name | Type | Req | Description |
|---|---|---|---|
| as_of | – | – | – |
| cik | – | – | – |
| include_provenance | boolean | – | – |
| include_ratios | boolean | – | – |
| ticker | – | – | – |
| year | integer | yes | – |
No output schema declared.
No examples provided.
get_financials_batch ~222
Retrieve normalized US-GAAP financials for MANY companies in one call — use this to compare peers or scan a set for a single fiscal year. Pass companies as comma-separated `tickers` (e.g. "AAPL,MSFT,GOOGL") and/or `ciks`; up to 25 symbols total, all for the same `year`. `as_of`, `include_provenance`, and `include_ratios` behave as in get_financials and apply to every symbol. Each company returns its own result — either `data` or an `error` with a recovery hint — so one bad symbol never fails the batch. The whole call counts as a SINGLE request against your monthly quota, so prefer it over many get_financials calls when you need several companies.
| Name | Type | Req | Description |
|---|---|---|---|
| as_of | – | – | – |
| ciks | – | – | – |
| include_provenance | boolean | – | – |
| include_ratios | boolean | – | – |
| tickers | – | – | – |
| year | integer | yes | – |
No output schema declared.
No examples provided.
get_usage ~71
Report the calling API key's current monthly quota: tier, monthly limit, requests used and remaining this billing month, and when it resets. Free to call — it does NOT consume quota. Check it before a large batch or a long run so you can pace requests and avoid a hard rate-limit (429).
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
list_filings ~134
List a company's recent SEC filings (newest first) from the EDGAR submissions index — a lean company header plus filing rows. Identify the company by `ticker` OR `cik`. Optionally filter by `form` (e.g. "10-K", prefix-matched so it includes amendments like "10-K/A") and cap the number of rows with `limit` (1-100). Use this to discover which fiscal years or filings are available before calling get_financials.
| Name | Type | Req | Description |
|---|---|---|---|
| cik | – | – | – |
| form | – | – | – |
| limit | integer | – | – |
| ticker | – | – | – |
No output schema declared.
No examples provided.
What is the Datavidence Financials MCP server?
Datavidence Financials is an MCP server listed in the public MCP registry as ai.datavidence/datavidence-financials. Normalized US-GAAP financial statements & fundamentals from SEC EDGAR, as MCP tools for LLM agents. This page covers its PyPI package (datavidence-financials).
Is the Datavidence Financials MCP server safe to use?
Datavidence Financials scores 67 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 21 September 2026. 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 Datavidence Financials MCP server expose?
Datavidence Financials exposes 4 tools: get_financials, list_filings, get_financials_batch, get_usage. Their descriptions and schemas cost roughly 625 tokens of context every time the server is loaded.
Is the Datavidence Financials MCP server still maintained?
Datavidence Financials is still listed as active in the MCP registry. We last reached this channel on 21 September 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 Datavidence Financials MCP server under?
Datavidence Financials declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.