Strong XBRL extraction for analysts — Valuein is built for programmatic and agent access.
Calcbench is a respected SEC XBRL data provider focused on detailed financial-statement extraction for human analysts. Both parse SEC EDGAR. Valuein differentiates on programmatic access, true point-in-time vintaging, agent-native delivery, and per-fact provenance.
The short version, including where Calcbench is the better pick.
Calcbench excels at deep, inline XBRL extraction in a web tool for analysts. Valuein is built for programmatic and AI-agent access: a Bulk Data API, Python SDK, and an agent-safe MCP serving 120.5M+ facts — each with a fact_id back to the filing — plus a true restatement vintage for backtesting.
Deep footnote / inline XBRL: Standardized concepts + audited ratios.
Calcbench has stronger inline XBRL extraction for detailed 10-Q footnotes
Quants and engineers who need clean, point-in-time time-series fundamentals in Parquet with programmatic and AI-agent access, rather than an analyst web tool.
What you get done, not just a feature checklist.
Grouped by what you are trying to do. Scroll sideways on a phone.
| Feature | Valuein | Calcbench |
|---|---|---|
| Data integrity and audit | ||
| Point-in-Time | Restatement vintage (accepted_at) | Snapshot-based PIT |
| Survivorship Bias | All delisted companies, all history | Active companies primary focus |
| Agents and workflow | ||
| AI Agent Access | Agent-safe MCP + expert agentic workflows | No MCP / agent surface |
| Access and pricing | ||
| Pricing | $0–$49–$499/month | Custom enterprise pricing |
| Format | Columnar Parquet — DuckDB/Spark native | Web tool, JSON/CSV endpoints |
Calcbench details and pricing are based on publicly available information as of June 2026 and may have changed; verify on their site. Where a competitor's figure is vendor-reported or estimated, we say so.
Install the SDK and read a company with no token and no card: the free sample runs the same code your plan will. Add a key later and nothing else changes.
from valuein_sdk import ValueinClient with ValueinClient() as client: # What a ticker or CIK resolves to. A CIK also reaches delisted companies. print(client.resolve(["AAPL", 320193])) # One company's rows from a table, with the point-in-time filter applied. facts = client.read_table( "fact", tickers="AAPL", columns=["standard_concept", "period_end", "fiscal_period", "numeric_value"], limit=10, ) print(facts) # Named SQL templates. Pass parameters as keyword arguments. print(client.list_templates()[:5]) df = client.run_template("fundamentals_by_ticker", ticker="AAPL") print(df.head()) # Links to the SEC filings behind the numbers. links = client.filing_links("AAPL", form_types=["10-K"], limit=3) print(links[["form_type", "filing_date", "document_url"]]) # Restatement Radar: figures a later filing changed (every plan). changed = client.restatements(ticker="AAPL", limit=5) print(changed[["standard_concept", "period_end", "first_value", "current_value", "disclosure_class"]])Start with the free sample. No card, no sales call; pricing is public.