Datavidence Financials

Datavidence Financials — MCP Server

Normalized US-GAAP financial statements for every SEC XBRL filer — point-in-time, as originally reported — as MCP tools for your AI agent (or a plain REST API).

Language models are good at reasoning about financial statements and bad at *getting* them. SEC EDGAR has the data, but its XBRL is a thicket of inconsistent tags, renamed concepts, and per-filer quirks — so agents either hallucinate the numbers or you spend weeks building a normalization layer. This is that layer: your agent asks for a company's financials and gets a clean, consistent answer — over the Model Context Protocol, or as a plain REST API.

⭐ If this is useful, please star the repo. It's a solo, early project, and stars are how other developers find it.

This is the open-source, AI-native layer for the Datavidence Financials API — a standalone stdio server that forwards over HTTPS to the REST API (bring your own key). The connector is MIT-licensed; the underlying API is a commercial service.

Try it in 30 seconds (no signup)

Run it with no clone using uv — it installs into a throwaway environment:

FL_API_KEY=sandbox_demo_key uvx datavidence-financials

sandbox_demo_key returns sample data with no signup — good for a first run. Set FL_API_KEY to your real key for live SEC data. The server speaks MCP over stdio, so an MCP client (e.g. Claude Desktop, below) launches it.

Or install it as a persistent tool with pipx:

pipx install datavidence-financials

FL_API_KEY=sandbox_demo_key datavidence-financials

Connect by URL (no install)

Clients that support remote MCP servers (streamable HTTP) can connect without installing anything:

Claude Code:

claude mcp add --transport http datavidence-financials \

https://mcp.financials.datavidence.ai/rapidapi/mcp \ --header "X-API-Key: YOUR_RAPIDAPI_KEY"

For the sample data, use the /mcp URL and leave out the header.

claude.ai: add https://mcp.financials.datavidence.ai/mcp as a custom connector with no sign-in. claude.ai can't send an API key for most accounts yet, so it gets the sample data for now.

Why it's different

• Point-in-time, as originally reported. Pass an as_of date and you get the figures as they stood then — no look-ahead bias from later restatements. The thing backtests quietly get burned without.
• Normalized to one schema. EDGAR's XBRL tags drift between filers and change over the years. We map them to a single US-GAAP income statement, balance sheet, and cash flow — including the awkward cases (noncontrolling interest, mezzanine/temporary equity, non-calendar fiscal years) — so you never parse a filing.
• Every SEC XBRL filer. Coverage is the whole SEC XBRL universe (~2009 to present), fetched and normalized on demand — any CIK with XBRL facts, not a curated subset.
• Source-linked, too. Turn on provenance and every value carries its SEC accession, filed date, and a direct EDGAR URL — so the model cites the filing instead of inventing a number.

Honest scope: US-GAAP only (IFRS filers return a clear "unsupported" signal rather than wrong numbers); XBRL-era history (~2009 onward). And when a company reorganizes under a new holding entity, SEC's ticker map points only at the successor CIK — the earlier years stay under the predecessor, so the error tells you and you pass cik= directly.

Tools

• `get_financials` — normalized income statement + balance sheet + cash flow for one company and fiscal year, from SEC EDGAR XBRL. Supports as_of (point-in-time, as originally reported), include_provenance (per-value SEC accession, filed date, and direct EDGAR source URL), and include_ratios (margins, ROA/ROE, leverage).
• `get_financials_batch` — the same, for up to 25 companies in one call (comma-separated tickers/CIKs). Per-symbol results; counts as a single quota unit, so one bad symbol never fails the batch.
• `list_filings` — a company's recent SEC filings (newest first) from the EDGAR submissions index; filter by form (e.g. 10-K). Use it to discover which fiscal years are available before calling get_financials.
• `get_revisions` — how a fiscal year's figures CHANGED across filings: every reported value with its filing date, form, SEC accession and EDGAR link, plus whether it was restated and by how much. Pfizer's FY2019 revenue was filed at $51.75B in 2020 and restated to $40.9B by 2022 — this is how you see that.
• `search_companies` — find a ticker and CIK by ticker or company name, for when you have "Berkshire" and need BRK-B. Use it before the tools above, which all require an identifier.
• `get_usage` — the key's monthly quota (tier, used, remaining, reset). Free to call; consumes no quota.

Errors surface the API's recovery_action hint, so agents self-correct.

Claude Desktop

Add to claude_desktop_config.json, then fully quit (Cmd+Q) and reopen Claude Desktop — the tools appear:

{

"mcpServers": { "datavidence-financials": { "command": "uvx", "args": ["datavidence-financials"], "env": { "FL_API_KEY": "sandbox_demo_key" } } } }

Then ask, e.g., *"Get AAPL's FY2023 income statement, balance sheet, and cash flow with ratios."* Swap in your real key for live data.

Codex

Add to ~/.codex/config.toml, then start codex — the tools appear:

[mcp_servers.datavidence-financials]

command = "uvx" args = ["datavidence-financials"] env = { FL_API_KEY = "sandbox_demo_key" }

uvx downloads the package on first run; allow more than Codex's 10 s default.

startup_timeout_sec = 30

Swap in your real key for live data.

Or connect by URL instead (nothing to install; set DATAVIDENCE_API_KEY to your RapidAPI key):

[mcp_servers.datavidence-financials]

url = "https://mcp.financials.datavidence.ai/rapidapi/mcp" bearer_token_env_var = "DATAVIDENCE_API_KEY"

Leave out bearer_token_env_var and use https://mcp.financials.datavidence.ai/mcp for the sample data.

Configuration (environment variables)

Getting live data

The demo key returns sample data. For live figures, grab a key on RapidAPI: Free (1,500 calls/mo), Pro ($29 / 50k), Business ($99 / 300k). Full feature parity across tiers — they differ only by monthly call volume.

To use your RapidAPI key, set these three variables (in the env block of the Claude Desktop config, or the env table in Codex's config.toml):

FL_API_BASE_URL=https://datavidence-financials-api.p.rapidapi.com

FL_API_KEY_HEADER=X-RapidAPI-Key FL_API_KEY=

Your key is on RapidAPI under your app's Authorization page, or in any code snippet on the API's page. Calls are metered by RapidAPI against your plan. With a RapidAPI key, get_usage shows your RapidAPI plan and its monthly limit; RapidAPI meters your calls, so check how many you've used in your RapidAPI dashboard.

Run from source

pip install -e .

FL_API_KEY=sandbox_demo_key python -m mcp_server.server # stdio transport

Tests

pip install -e ".[dev]"

pytest

29 tests, no network and no API key needed. They call every tool through the MCP SDK with the HTTP layer stubbed, check that an API error reaches the model with its recovery hint, and check that each tool declares all four behaviour hints (read-only, non-destructive, idempotent, open-world).

Privacy Policy

The connector runs on your machine, has no telemetry and stores nothing. When a tool is called it sends two things to the Datavidence Financials API: the tool's arguments (for example a ticker, a CIK, a fiscal year or a company-name search) and your API key, in a request header. It does not see your files or the rest of your conversation.

• Where it goes: https://api.financials.datavidence.ai by default. If you set FL_API_BASE_URL to the RapidAPI gateway, requests go through RapidAPI, under its own privacy policy.
• What the API records: for each request, the endpoint, HTTP status, response time, timestamp and IP address, tied to a hash of the API key (never the key itself).
• Retention: usage logs are kept for 12 months.
• Sharing: not sold; shared only with the marketplace gateway you subscribed through and the infrastructure provider that hosts the service.
• Contact: admin@datavidence.ai

Full policy: https://financials.datavidence.ai/privacy

Feedback

Found a company where the numbers come back wrong, or a field/tool you need? [Open an issue](https://github.com/datavidence/datavidence-financials-mcp/issues) — the normalization edge cases are exactly the feedback that makes this better, and I read every one.

Links

• Site & docs: https://financials.datavidence.ai
• MCP quickstart: https://financials.datavidence.ai/mcp
• MCP registry: ai.datavidence/datavidence-financials
• PyPI: https://pypi.org/project/datavidence-financials/
• Get a key (RapidAPI): https://rapidapi.com/datavidence-ykNLbvGmT/api/datavidence-financials-api
• Privacy policy: https://financials.datavidence.ai/privacy
• Terms of service: https://financials.datavidence.ai/terms
• Security: see SECURITY.md to report a vulnerability privately.

License

MIT © 2026 Datavidence LLC — see LICENSE. The connector is open-source; the underlying Datavidence Financials API is a commercial service.