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Octus Connected ChatGPT and Claude with Professional Credit Data: The End of Manual Searching in Finance

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The world of finance is built on precise data — and on the speed of its interpretation. But what if instead of spending hours searching through databases, an analyst could simply ask a question in natural language in Claude or ChatGPT and receive a verified answer backed by original documents? That's exactly what the Octus MCP Connector enables as of July 14, 2026 — a new tool that, for the first time in history, brings professional credit data directly into the environment of large language models.

What Octus is and why the global credit market relies on it

Octus (formerly known as Reorg) is a platform relied upon by 40,000 professionals from investment banks, law firms, and asset managers worldwide. Its uniqueness lies in the combination of three factors: a 350-member team of financial analysts and journalists, proprietary data covering more than 95% of the sub-investment grade credit market, and technology that processes this data into actionable insights.

Each year, Octus publishes over 55,000 analytical articles and manages more than 8 million private documents from data rooms. Its data is used by all of the world's Top 10 asset managers and CLO managers.

MCP: The protocol breaking down walls between AI and corporate data

The Model Context Protocol (MCP) is an open standard developed by Anthropic that allows large language models to securely connect to external data sources. Instead of every company having to build its own integration between its data and each AI model separately, MCP defines a unified interface — similar to USB for hardware.

Thanks to MCP, Claude, ChatGPT, and other LLMs can now retrieve data in real time from corporate systems, databases, and specialized platforms like Octus. For the financial sector, this means the end of the era of manually switching between windows — an analyst asks a question in the language they normally speak and gets an answer backed by current, verified data.

What Octus MCP Connector can do in practice

Under the hood of the connector runs CreditAI by Octus — a proprietary AI engine that interprets natural language queries and connects them with relevant data sources. Every answer includes a citation of the original source, so the analyst can verify where the information comes from with a single click.

The connector provides access to five key datasets:

  • Octus Credit Intelligence — 55,000+ analytical articles per year covering the entire credit lifecycle from primary issuances to restructurings
  • Fundamental data on liquid and private credit — financial statements, capital structures, and transcripts for 95%+ of the credit market
  • FinDox — 8 million private documents from data rooms with auditable access control for material non-public information (MNPI)
  • Private company analysis — decade-long financial series and capital structures of private companies with bank loans and bonds
  • Deal Term Analytics — 170+ covenant data fields on each instrument across syndicated loans and direct lending deals

Five scenarios where MCP Connector rewrites the rules of the game

1. Agentic credit research: Ask a question in Claude or ChatGPT and get an answer backed by news, fundamental data, and documents from FinDox. Custom AI agents can fully automate these workflows.

2. Automated deal terms benchmarking: The connector can scan covenant data across hundreds of comparable deals, automatically flag deviations from market standard, and generate a structured credit memo. What used to take hours now happens in seconds.

3. Accelerated legal due diligence: Lawyers gain direct access to historical credit agreements and documentation packages. They can search precedents using natural language and speed up contract preparation.

4. Restructuring and business development: By connecting Octus data with internal CRM systems, an automated pipeline emerges that uncovers refinancing and restructuring opportunities before competitors register them.

5. Portfolio surveillance: Programmatic querying of covenants, financial data, and research enables automated screening of the entire sub-investment grade market with instant "pass," "watch," and "breach" signal flags.

Security and permissions: The key question for financial data

Given the sensitivity of financial information, Octus has implemented a robust security layer. The connector uses OAuth 2.0 with PKCE for authenticated access — every query is encrypted and tied to the permissions of a specific user. MNPI exposure is auditable and access rights are automatically synchronized with existing permissions within the Octus subscription.

This is a fundamental difference compared to public AI tools — Octus MCP Connector functions as a permissioned golden copy, meaning a single, authoritative source of data that only those with the right permissions can access.

What this means for Czech and European financial professionals

Octus MCP Connector is available to all existing Octus platform subscribers — at an additional cost to the current subscription. For European financial institutions, this means several things:

First, in the context of the EU AI Act, it is crucial that every AI output includes source attribution. Octus meets this requirement — every answer is traceable to the original document, which is exactly the type of transparency that European regulation demands.

Second, the connector also supports custom agentic AI platforms — European banks and funds building internal AI agents can connect them directly to Octus without needing their own integrations.

Third, MCP as an open standard means that European financial houses are not vendor-locked to a single AI model. The connector works with Claude, ChatGPT, and any other MCP-compatible model, creating room for European LLM alternatives such as Mistral.

The broader trend: Agentic AI is transforming the financial sector

Octus is not the only one bringing AI to the world of finance. In May 2026, Anthropic introduced ten specialized financial agents for banks and investors (Anthropic Finance Agents). TD Bank cut mortgage approval from 15 hours to 3 minutes using agentic AI. And Robinhood launched agentic trading, where AI independently buys stocks.

Octus MCP Connector fits into this trend as data infrastructure — without verified, current data, even the smartest AI agents are useless. Octus delivers the deepest and most verified source of credit information on the market.

Pricing and availability

Octus MCP Connector is available immediately for all existing Octus subscribers. The exact price is not public — it depends on the scope of the subscription and is handled individually through an account manager. Octus also offers trial access for those interested via the registration form on their website. Technical integration guides for developers are freely available on the connector's product page.

How does MCP Connector differ from regular search in ChatGPT or Claude?

Standard language models respond based on the data they were trained on — which may be outdated or unverified. Octus MCP Connector, on the other hand, accesses current proprietary data in real time and provides a citation of the original source with every answer. This allows the analyst to immediately verify that the answer is based on a specific document, not on the model's general "knowledge."

Is MCP Connector suitable for smaller investment firms or only for large institutions?

Technically, the connector is part of an Octus subscription, which is primarily used by medium and large financial institutions. Octus serves more than 40,000 users, and its clients include all ten of the world's largest asset managers. For smaller boutique firms, the key question is the cost-benefit ratio — if a firm works intensively with credit data, MCP Connector can fundamentally accelerate analytical workflows regardless of team size.

Does Octus MCP Connector support languages other than English, such as Czech?

The connector itself works with data that is primarily in English (credit documents, financial statements, analytical articles). However, you can ask questions in any language understood by the target language model (Claude, ChatGPT support Czech as well). The answers will contain English source citations, but the explanation and analysis itself will be delivered in Czech — depending on the language you use to ask the model.

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