Dexter Jp
FreemiumAI-powered financial research platform for all 4,631 Japanese listed companies with free API/MCP.
By Tanmay Verma, Founder · Last verified 05 Jul 2026
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Added 4d ago
77/100Safe BetIn short
Dexter Jp — AI-powered financial research platform for all 4,631 Japanese listed companies with free API/MCP. Best for Individual investors researching Japanese equities with fundamental analysis, Quant analysts building models using structured financial data, AI developers integrating real-time financial data into agent workflows. Free to start; paid plans from $4980/mo.
Is Dexter Jp actually worth it?
LiveSee what real users actually say. We scan live discussions, reviews and complaints across the web and hand you an honest verdict — in under a minute.
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Editorial Verdict
Best for
Individual investors researching Japanese equities with fundamental analysisQuant analysts building models using structured financial dataAI developers integrating real-time financial data into agent workflowsAcademics studying Japanese corporate finance with free high-volume accessPortfolio managers needing traceable, auditable data from source filings
Not ideal for
Traders needing real-time or intraday price dataUsers requiring non-Japan equities coverageThose without basic financial literacy for independent interpretationTeams that need advanced charting or technical analysisUsers who cannot read Japanese (some UI and documentation in Japanese)
EDINET DB delivers an unmatched combination of breadth (4,631 companies), depth (147 indicators), and AI-native access via MCP—all with a generous free tier. The deterministic parsing and traceability to source EDINET documents address a real pain point in financial data trustworthiness. It's a no-brainer for anyone serious about Japanese equity research, though real-time traders should look elsewhere.
Compare with: Dexter Jp vs GeologicAI, Dexter Jp vs Mineral (Alphabet X), Dexter Jp vs Robin AI
Last verified: July 2026
What's new in Dexter Jp
Checked 2 days agoAcross the latest 8 updates: 5 feature updates, 1 launch and 2 news mentions.
LaunchBlog·2 days agoNewest
姉妹サービス「FUDOSAN DB」が正式版になりました
不動産データ構造化サービス「FUDOSAN DB」正式版公開。EDINET DBユーザー向け特典を7/20まで提供。
FeatureBlog·5 days ago
Claude Fable 5 に上場4,000社の有報を渡して放置した記録
Claude Fable 5で減損リスク兆候を探索するデモ。175秒・11回のツール実行でSonnet 5との差を示す。
FeatureBlog·14 days ago
経営者の生の言葉を構造化検索する — EDINET DBの決算説明会Q&Aデータ
決算説明会Q&Aを806社・12,139セクション保有。MCP/REST APIで業種横断検索可能。
NewsBlog·17 days ago
防衛省関連の事業費は、どの上場企業に紐づくか — 政策資金と決算をAIで縦串する
政策資金データとEDINET DBを横断し、防衛費の上場企業への影響を分析する方法を解説。
NewsBlog·22 days ago
SpaceXは上場した。日本の宇宙ビジネスはどこまで来たか
SpaceX上場を機に、政策資金と決算データを用いて日本の宇宙ビジネスを縦串分析する手順を紹介。
FeatureBlog·May 19
J-Quants × EDINET DB 完全ガイド (2026年5月版)
J-Quants株価とEDINET DB有報財務指標を組み合わせ、AIエージェントから自然言語分析する方法を解説。
FeatureBlog·May 19
GPT-5.5 Codex × EDINET DB: 上場約4,400社のデータをAIエージェントで分析
GPT-5.5 CodexとEDINET DB MCP 48ツールでスクリーニング・沿革分析・政策保有可視化を実演。
FeatureBlog·May 19
Claude Codeで日本株データを自由に分析する (2026年5月版)
Claude CodeとEDINET DB MCP 48ツールを組み合わせた日本株分析の実例集。沿革246K eventsなどをカバー。
What independent users actually report about Dexter Jp
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
18 mentions across 2 sources (GitHub, Lemmy).
45% positive55% critical
Recurring strengths
- +Covers all 4,631 Japanese listed companies including 797 delisted ones.
- +Deterministic XBRL parsing with no LLM hallucination on financial numbers.
- +Free tier offers 100 API/MCP requests per day with no credit card.
- +MCP server enables direct integration with Claude Desktop, Claude Code, ChatGPT.
- +Academy plan gives academic researchers 1,000 requests/day.
Recurring frustrations
- −TUI has a bug causing duplicate prompt submissions after interrupts.
- −Large JSON responses overwhelm low-cost LLMs like Ollama.
- −Sparse community feedback makes support and reliability uncertain.
- −Web dashboard less intuitive for non-technical users.
- −API documentation could be more comprehensive for beginners.
Patterns worth knowing
AI agent integration via MCP is novel but requires technical setup
Seen on GitHub, Lemmy
Low-cost LLM performance is hindered by large JSON payloads
Seen on GitHub
TUI stability issues undermine productivity
Seen on GitHub
Learning curve
intermediateProductive in ~A few hours
Hidden costs people mention
- • No obvious hidden costs, but advanced features like Slack integration require paid plans
Viability Score
77/100
Safe BetHow likely is Dexter Jp to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
momentum
55
funding runway
80
website health
90
wrapper dependency
100
Last calculated: July 2026
How we score →Key Features
- Financial data for 4,631 listed Japanese companies (3,834 active, 797 delisted from FY2011–FY2026)
- 147 standardized financial indicators across JP GAAP, IFRS, US GAAP
- Rule-based Financial Health Score (0-100)
- Claude-generated AI integrated analysis (quantitative + qualitative)
- REST API with 69+ endpoints
- MCP server for direct AI agent integration (Claude Desktop, Claude Code, ChatGPT, OpenAI Codex CLI, Cursor)
- Web dashboard with rankings, screeners, and peer comparison
- Daily data updates at 8:00 JST
- Full traceability to original EDINET documents via docID
- Earnings call Q&A data for 806 companies, 12,139 sections, 29 theme tags
- Fundamental rankings (ROE, PBR, dividend yield, etc.) and IR theme screeners
- Sister service FUDOSAN DB for real estate data
- Academy plan for researchers (1,000 requests/day)
- J-Quants integration for combined price and fundamental analysis
- Coverage from FY2011 to FY2026, up to 6 years of data per company
About Dexter Jp
FreemiumIntermediateAPI availableWeb · API
EDINET DB is a specialized AI research agent that transforms Japanese EDINET filings into structured, actionable financial data. It provides free access to financial metrics, AI-generated analysis, and a REST API/MCP server for all 4,631 Japanese listed companies (3,834 active + 797 delisted). The platform ingests XBRL filings daily from Japan's EDINET system, normalizing across JP GAAP, IFRS, and US GAAP into 147 standardized fields. A rule-based engine computes a Financial Health Score (0-100), and Claude generates integrated AI assessments combining quantitative data with qualitative insights from filings. Key features include full traceability to source EDINET documents, deterministic parsing (no LLM hallucinations on numbers), daily updates at 8:00 JST, and a free tier with 100 API/MCP requests per day. The MCP server enables direct integration with AI agents like Claude Desktop, Claude Code, ChatGPT, and OpenAI Codex CLI. The web dashboard offers rankings, screeners, peer comparison, and earnings call Q&A data covering 806 companies with 29 theme tags. A sister service FUDOSAN DB for real estate data is also available. Pricing includes a free tier, a new Light plan for dashboard-focused users at ¥1,480/month introductory (regular ¥2,480), Pro at ¥4,980/month, Business at ¥29,800/month, and Enterprise (custom). An Academy plan offers 1,000 requests/day for academic researchers with .ac.jp/.edu emails. All plans include REST API and MCP access, with varying request limits, dashboard modules, export, notifications, and Slack integration. Compared to competitors like J-Quants or alternative data providers, EDINET DB's edge is its integration with AI agents via MCP, deterministic traceability, and broad coverage of delisted companies. It's best for investors, analysts, developers, and researchers who need deep, verifiable financial data on Japanese equities.
Behind the Verdict
We'd reach for EDINET DB when we need structured, auditable financials on nearly every Japanese listed company—including delisted ones—without the typical data vendor lock-in. The MCP server is a genuine differentiator: hook it into Claude or ChatGPT and you're asking questions like 'show me all companies with improving ROE and low debt' in natural language, getting answers grounded in 147 standardized fields. The deterministic parsing means you won't get hallucinated numbers—each data point links back to the EDINET source PDF. Where it bites: this is not a platform for day traders or anyone who needs real-time price data. It's fundamentally a fundamental research tool, and while the earnings call Q&A data (806 companies, 29 theme tags) adds qualitative depth, the absence of technical indicators or charting limits its appeal to a certain investor type. The interface is utilitarian—functional but not pretty. And if you can't read Japanese, some navigation and explanatory text remain in Japanese, though the core data is universally structured. Compared to J-Quants, which also offers Japanese stock data, EDINET DB goes deeper into accounting fundamentals and offers free API access, while J-Quants focuses more on quantitative factor models and price data. J-Quants is a better fit for algo-trading; EDINET DB wins for fundamental analysis and AI agent integration. In practice, the free tier (100 requests/day) is generous enough for a serious retail investor to test a few dozen companies daily. The Light plan at ¥1,480/month (introductory) unlocks full dashboard features if you don't need heavy API usage. For developers building a research tool or a quant model, the Pro plan at ¥4,980/month gives 1,000 requests/day—plenty to run batch screening. The recent
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Use Cases
- Screen Japanese stocks by ROE, PBR, dividend yield, and other fundamentals using the web dashboard or API.
- Generate AI-powered integrated analysis of a company's financial health using Claude through MCP.
- Combine EDINET DB financial data with J-Quants stock prices for quantitative research.
- Build custom AI agents that query Japanese company filings via MCP server.
- Track peer comparisons and rankings across 147 financial indicators.
- Analyze IR themes (e.g., PBR response, DX/AI strategy) using thematic screeners.
Models Under the Hood
claude-3.5-sonnetclaude-fable-5gpt-5.5
Limitations
- REST API and MCP requests are limited to 100/day on the Free plan, scaling to 1,000/day on Pro.
- Operating profit data is not available for some IFRS/US GAAP filers due to missing standard XBRL elements.
- The platform is entirely focused on Japanese listed companies, with no coverage of other markets.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Annual total
—
Contact sales for a quote
Effective monthly
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Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Integrations
Resources & Guides
- Resourceedinetdb.jp
Claude Fable 5 Dexter Jp · Dexter Jp
Helpful link from edinetdb.jp
- Resourceedinetdb.jp
Claude Code Japan Stock Data 2026 05 · Dexter Jp
Helpful link from edinetdb.jp
- Resourceedinetdb.jp
J Quants Edinet Db Complete Guide 2026 05 · Dexter Jp
Helpful link from edinetdb.jp
- Resourceedinetdb.jp
Gpt 5 5 Codex Edinet Db 2026 05 · Dexter Jp
Helpful link from edinetdb.jp
- Resourceedinetdb.jp
Edinet Xbrl Structuring 4 Challenges · Dexter Jp
Helpful link from edinetdb.jp
Frequently Asked Questions
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