SEC EDGAR fundamentals, ratios, valuation, and filings for AI agents. Point-in-time safe.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Point-in-time, survivorship-free SEC fundamentals β built for AI agents, safe enough for institutions that fear AI. Every number is born in a filing and carries a
fact_id; the model never mints a digit. Streamed as Parquet, queried with DuckDB or natural language, reproducible run to run.
This repository is the public home and discovery hub for the Valuein data platform. It hosts the documentation, examples, notebooks, and the MCP registry manifest used by AI agents to find us. Source code for the SDK, MCP server, and data pipeline lives in dedicated repositories β this is the front door.
| You want to⦠| Go to |
|---|---|
| Try the SDK in 30 seconds without a token | Quickstart |
| See every channel we ship through | Distribution channels |
| Check pricing and what each plan unlocks | Plans & access |
| See why AI agents are first-class citizens here | Built for AI agents |
| Connect an AI agent (Claude, Copilot, ChatGPT, Cursorβ¦) | MCP for AI agents |
| Set up the Workspace by role (analyst, PM, quant, creator) | docs/WORKSPACE_GUIDE.md |
| Read the data model | Data model |
| Find a quick recipe by role | Recipes by role |
| Run end-to-end Python examples | examples/python/ |
| Run interactive notebooks (Colab) | examples/notebooks/ |
| Read the methodology / SLA / compliance | Documentation |
| Report a data error or request a feature | Support & community |
| Contribute an example or notebook | CONTRIBUTING.md |
Survivorship-bias-free, point-in-time US fundamentals sourced directly from SEC EDGAR.
standard_concept values plus 164 materialized financial ratios (FY + TTM); unmapped tags are exposed under 'Other' rather than droppedfiling_date and millisecond-precision accepted_at| Property | What it means for you |
|---|---|
| π Point-in-time | filing_date <= trade_date removes look-ahead bias. accepted_at gives intraday resolution for same-day signals. |
| βοΈ Survivorship-bias free | Delisted, bankrupt, and acquired companies remain in every snapshot β your backtest sees the universe the market saw. |
| π Standardized concepts | Both the raw XBRL tag (fact.concept) and the canonical name (fact.standard_concept) are on every row. No hidden mapping table. |
| π CPA-verified catalog | Every standard_concept carries a review_confidence β 1.0 once an accountant has signed off on its name, statement and rule (then it's locked; the pipeline only ever adds new concepts, never mutates a verified one), 0.7 while provisional. Filter review_confidence >= 1.0 for the labels analysts, quants and AI models can agree on and train against. |
| π DuckDB-native | Millisecond analytics over remote Parquet via httpfs. Zero database provisioning. |
| π Append-only restatements | A 10-K/A adds a new row β the original stays. Reconstruct the as-reported view of any historical date. |
| π§Ύ Measured, published accuracy | Mathematical consistency checked against published, cited accounting identities β CI-gated, and re-derivable yourself with one DuckDB command. The current measured figure lives in docs/accuracy/baseline.json. |
| π One token, every channel | The same Bearer token authenticates the SDK, MCP server, and bulk-data API. |
Valuein is MCP-first and agent-agnostic: the same typed tool surface works in Claude, Copilot, ChatGPT, Perplexity, Gemini, Grok, Cursor, or your own LangGraph / CrewAI agent. The design goal is simple β the model never mints a number. Numbers are born in tools, carried as provenance-tagged facts, and the model is only allowed to arrange words around figures it was handed.
| Guarantee | How it's enforced |
|---|---|
| Fact-level lineage | Every figure a tool returns carries a fact_id and its source filing; verify_fact_lineage round-trips any fact_id back to the exact SEC filing URL in one call. |
| Zero look-ahead | Every time-series tool accepts as_of_date and reconstructs the information set as of that date β the same PIT discipline the Parquet layer enforces for backtests. |
| Reproducible runs | Deterministic, idempotent tools: same inputs, same output. No rolling windows, no hidden "latest". Agents can cache, retry, and replay; you can reproduce a run later. |
| Agent-agnostic state | Theses, claims, watchlists, signals, and reports persist server-side across sessions and across clients β save a thesis from Claude today, list it from Cursor tomorrow. |
| Human-on-the-loop (HOTL) | Mutating and outward-facing tool actions go through a staged-action approval ledger: the agent proposes, a human approves, and the decision lands in an immutable audit entry. Read-only tools never stage. |
| Governed managed runs | Server-side managed agent runs execute at temperature 0 with a model allow-list and destructive-tool stripping β reproducible research, not improvisation. |
| Graded track records | Saved theses and claims are scored against subsequent fundamentals and prices; publishing builds a public, verifiable track record β your agent keeps score. |
The full tool reference is in docs/MCP_TOOLS.md; agent-facing runtime instructions are in AGENTS.md.
The same dataset, delivered four ways so it lands where you already work.
| Channel | Audience | Endpoint / install |
|---|---|---|
| Python SDK | Quants, engineers, data scientists | pip install valuein-sdk Β· PyPI |
| MCP server | AI agents (Claude, Copilot, ChatGPT, Cursor, custom) | https://mcp.valuein.biz/mcp Β· server.json |
| Web dashboard | Retail, executives, non-technical users | valuein.biz |
| Bulk data API | B2B partners, fintech platforms | https://data.valuein.biz Β· contact us |
A single Stripe-issued token unlocks every channel at your tier β no per-channel billing.
Pricing and feature scope are mirrored from valuein.biz/pricing β the website is the source of truth and our checkout flow routes to the correct Stripe product.
| Plan | Universe | History | Data freshness | Price | Get it |
|---|---|---|---|---|---|
| Sample | S&P 500 (~500 tickers) | 5-year window | Quarterly snapshots | Free Β· no signup | Just pip install valuein-sdk |
| Free | S&P 500 (~500 tickers) | 1993 β present | Daily | Free Β· register | Register |
| Pro | Full active + delisted US universe (19,000+ entities) β fundamentals dataset only | 15-year rolling (2011 β present) | 24h after SEC | $49 / mo Β· $490 / yr | Subscribe |
| Institutional | Same universe + smart-money dataset (insider transactions on Forms 3/4/5/144 + institutional ownership on Forms 13F/13D/13G) | 1993 β present (unlimited) | 4h priority + filing-event webhooks | $499 / mo Β· $4,790 / yr | Subscribe |
| Enterprise | Negotiated Β· dedicated infrastructure Β· expanded redistribution scope | Custom | Real-time 8-K + zero-retention option | Talk to us | sales@valuein.biz |
Each tier removes a different buyer objection β Pro removes the universe + history limits on the fundamentals dataset; Institutional adds the smart-money dataset (insider transactions + institutional ownership), unlimited history back to 1993, filing-event webhooks, and a commercial redistribution license under a business-hours SLA; Enterprise adds dedicated infrastructure and bespoke contracts.
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