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  3. MCP Sec Edgar
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MCP Sec Edgar

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time β€” check back soon.
View RepositoryVisit Website

SEC EDGAR fundamentals, ratios, valuation, and filings for AI agents. Point-in-time safe.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "mcp-sec-edgar": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-sec-edgar"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’° More in Finance & Fintech

Documentation Overview

Valuein

PyPI version PyPI downloads Python 3.10+ License: Apache 2.0 GitHub stars MCP Registry Docs

Valuein β€” SEC EDGAR fundamentals for analysts, quants, and AI agents

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.

Terminal
pip install valuein-sdk          # data for code
# or add this URL to any MCP-capable AI client:
# https://mcp.valuein.biz/mcp     # data for agents

What's in here

You want to…Go to
Try the SDK in 30 seconds without a tokenQuickstart
See every channel we ship throughDistribution channels
Check pricing and what each plan unlocksPlans & access
See why AI agents are first-class citizens hereBuilt for AI agents
Connect an AI agent (Claude, Copilot, ChatGPT, Cursor…)MCP for AI agents
Set up the Workspace by role (analyst, PM, quant, creator)docs/WORKSPACE_GUIDE.md
Read the data modelData model
Find a quick recipe by roleRecipes by role
Run end-to-end Python examplesexamples/python/
Run interactive notebooks (Colab)examples/notebooks/
Read the methodology / SLA / complianceDocumentation
Report a data error or request a featureSupport & community
Contribute an example or notebookCONTRIBUTING.md

The data product

Survivorship-bias-free, point-in-time US fundamentals sourced directly from SEC EDGAR.

  • 12M+ filings β€” 10-K, 10-Q, 8-K, 20-F, 40-F, and amendments since 1993
  • 111M+ standardized facts across 19,000+ US public companies β€” including every bankruptcy, merger, and delisting since 1993
  • 11,966 raw XBRL tags normalized to 292 canonical standard_concept values plus 164 materialized financial ratios (FY + TTM); unmapped tags are exposed under 'Other' rather than dropped
  • 20 Parquet tables β€” 14 core (fundamentals, ratios, valuations, index membership, daily OHLCV price history with adjusted close) + 6 smart-money tables (Institutional tier)
  • Cloud Parquet on Cloudflare R2 β€” stream with DuckDB; no database setup, no local downloads
  • PIT-correct β€” every fact carries filing_date and millisecond-precision accepted_at

Why it's different

PropertyWhat it means for you
πŸ•’ Point-in-timefiling_date <= trade_date removes look-ahead bias. accepted_at gives intraday resolution for same-day signals.
βš–οΈ Survivorship-bias freeDelisted, bankrupt, and acquired companies remain in every snapshot β€” your backtest sees the universe the market saw.
πŸ“Š Standardized conceptsBoth the raw XBRL tag (fact.concept) and the canonical name (fact.standard_concept) are on every row. No hidden mapping table.
πŸ” CPA-verified catalogEvery 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.
πŸš€ DuckDB-nativeMillisecond analytics over remote Parquet via httpfs. Zero database provisioning.
πŸ” Append-only restatementsA 10-K/A adds a new row β€” the original stays. Reconstruct the as-reported view of any historical date.
🧾 Measured, published accuracyMathematical 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.
πŸ” One token, every channelThe same Bearer token authenticates the SDK, MCP server, and bulk-data API.

Built for AI agents

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.

GuaranteeHow it's enforced
Fact-level lineageEvery 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-aheadEvery 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 runsDeterministic, 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 stateTheses, 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 runsServer-side managed agent runs execute at temperature 0 with a model allow-list and destructive-tool stripping β€” reproducible research, not improvisation.
Graded track recordsSaved 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.


Distribution channels

The same dataset, delivered four ways so it lands where you already work.

ChannelAudienceEndpoint / install
Python SDKQuants, engineers, data scientistspip install valuein-sdk Β· PyPI
MCP serverAI agents (Claude, Copilot, ChatGPT, Cursor, custom)https://mcp.valuein.biz/mcp Β· server.json
Web dashboardRetail, executives, non-technical usersvaluein.biz
Bulk data APIB2B partners, fintech platformshttps://data.valuein.biz Β· contact us

A single Stripe-issued token unlocks every channel at your tier β€” no per-channel billing.


Plans & access

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.

PlanUniverseHistoryData freshnessPriceGet it
SampleS&P 500 (~500 tickers)5-year windowQuarterly snapshotsFree Β· no signupJust pip install valuein-sdk
FreeS&P 500 (~500 tickers)1993 – presentDailyFree Β· registerRegister
ProFull active + delisted US universe (19,000+ entities) β€” fundamentals dataset only15-year rolling (2011 β†’ present)24h after SEC$49 / mo Β· $490 / yrSubscribe
InstitutionalSame universe + smart-money dataset (insider transactions on Forms 3/4/5/144 + institutional ownership on Forms 13F/13D/13G)1993 – present (unlimited)4h priority + filing-event webhooks$499 / mo Β· $4,790 / yrSubscribe
EnterpriseNegotiated Β· dedicated infrastructure Β· expanded redistribution scopeCustomReal-time 8-K + zero-retention optionTalk to ussales@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.

Pay-per-call (MPP)

Read the full README β†’View source on GitHub β†’

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Frequently Asked Questions about MCP Sec Edgar

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "mcp-sec-edgar": { "command": "npx", "args": ["-y", "mcp-sec-edgar"] } }

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Technical Specs & Signals

CategoryπŸ’°Finance & Fintech
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
Views0
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Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

Not scored for repo-hosted servers β€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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