Matches you on PIT + survivorship — Valuein adds fact-level audit and an agent-safe MCP.
Sharadar's Core US Fundamentals (SF1) on Nasdaq Data Link is the quant gold standard for cheap, explicit point-in-time, survivorship-free fundamentals (as-reported and most-recent dimensions, next-trading-day availability). Valuein matches the PIT + survivorship story and adds per-fact filing lineage and a first-party agent-safe MCP.
The short version, including where Sharadar (Nasdaq Data Link) is the better pick.
Against Sharadar, point-in-time and survivorship-free are not the differentiator — Sharadar does both well. The edge is verifiability and AI-nativeness: Sharadar gives you a standardized value with no link to the underlying filing, while Valuein attaches a fact_id to every number for one-click verification, and ships a first-party MCP with safety guardrails (Sharadar has no real MCP).
Point-in-time, survivorship-free: Yes — accepted_at vintage.
Sharadar is a mature, widely-adopted, explicitly point-in-time and survivorship-free dataset — it matches Valuein on those claims
Quants who value Sharadar's PIT + survivorship rigor but also want fact-level filing provenance and a first-party, agent-safe MCP for AI-driven research.
What you get done, not just a feature checklist.
Grouped by what you are trying to do. Scroll sideways on a phone.
| Feature | Valuein | Sharadar (Nasdaq Data Link) |
|---|---|---|
| Data integrity and audit | ||
| Per-fact Audit Trail | fact_id → exact filing | datekey / RESTATED flag, no filing link |
| Agents and workflow | ||
| AI Agent Access | First-party MCP + agentic workflows + safety | No SF1 MCP support |
| Agent Workspace | Theses / claims / reports persist across AI clients | Dataset only |
| Access and pricing | ||
| Pricing transparency | Public $0 / $49 / $499 | Login-gated pricing |
| Delivery | SDK + Bulk API + MCP + Parquet | Nasdaq Data Link Python lib, bulk export |
Sharadar (Nasdaq Data Link) 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"]])Two reasons: verifiability and AI-nativeness. Sharadar gives a standardized value with no link to the source filing; Valuein attaches a fact_id to every number for one-click verification. And Valuein ships a first-party agent-safe MCP — Sharadar has no real MCP for SF1.
Both are genuine, restatement-aware, next-trading-day point-in-time models. Sharadar is the established standard; Valuein matches it and adds fact-level provenance and an agent-safe workspace on top.
Start with the free sample. No card, no sales call; pricing is public.