Finance & Accounting · Financial Datasets + Claude
Financial Datasets MCP with Claude: Faster Research and Reporting from Normalised Market Data
The short answer
Claude works with Financial Datasets through the Model Context Protocol (MCP), a secure standard that lets Claude read data from the service and run approved queries. Once connected with an API key, Claude can retrieve company financial statements, locate SEC filings, pull market time series and calculate financial ratios from a plain-English request, within permissions your organisation sets.
What is Financial Datasets?
Financial Datasets is a data service that provides company fundamentals, financial statements, SEC filings, ownership information, macroeconomic series and analytics. It supplies normalised financial and market data, meaning figures are organised consistently so they can be compared across companies and periods. Typical users include research analysts, finance teams, investment operations staff and developers building reporting or automation tools that depend on reliable financial information.
How Claude connects to Financial Datasets through MCP
The Model Context Protocol (MCP) is an open standard that lets Claude use other software securely. Think of it as a universal adapter between Claude and a tool. It allows Claude to read information and take actions, and the organisation decides exactly what Claude is allowed to access.
Once Financial Datasets is connected, Claude can typically look up a company's fundamentals, retrieve the latest filings, query market time series and compute ratios such as margins or leverage. A question like 'compare operating margins for these five companies over eight quarters' can be answered in one step, with the underlying figures shown.
Access is controlled through the API key you provide, which can be scoped and rotated by your IT team. Consequential actions, such as writing results into a reporting system, can be set to require a person's approval first, and every request can be logged for audit.
What you can automate
Equity research summaries
Analysts ask Claude for a structured summary of a company's recent results, drawn directly from its financial statements. Claude can compare revenue, margins and cash flow against prior periods and flag unusual movements. The analyst reviews the draft and adds their own judgement before it reaches a client or committee.
SEC filing monitoring
Claude can check for newly published SEC filings for a watch list of companies and highlight sections that changed, such as risk factors or management commentary. Compliance and research teams receive a short digest rather than opening every filing manually, which saves time during busy reporting periods.
Ratio analysis for credit reviews
Credit teams often need the same set of ratios for many borrowers. Claude can calculate leverage, interest cover and liquidity ratios from normalised data, present them in a consistent format and note where a figure appears to be missing or out of line, so a credit officer can focus on the decision.
Macro dashboard commentary
Economists and treasury staff can have Claude pull macroeconomic series, such as inflation or interest rate data, and draft a short commentary explaining recent trends. The team checks the figures and wording before the update is circulated internally.
Investor reporting pack preparation
Finance teams preparing board or investor packs can use Claude to gather fundamentals and market figures for the reporting period and lay them out in an agreed template. Each number carries its source, which makes the reviewer's checking faster and more reliable.
An end-to-end workflow: Quarterly peer benchmarking for the investment committee
TriggerThe investment team adds a new quarter's results to its tracked peer group in the shared tracker.
Claude retrieves the latest fundamentals and financial statements for each peer company from Financial Datasets.
Claude calculates agreed ratios such as gross margin, net debt to EBITDA and free cash flow yield.
Claude compares the figures with the prior four quarters and identifies the largest changes.
Claude writes the benchmarking table and a short narrative and saves a draft to the shared drive in Microsoft 365.
An analyst reviews the draft, corrects anything unusual and approves it for the committee pack.
OutcomeTypically, the benchmarking pack that once took an analyst most of a day can be prepared in under an hour, with a reviewer confirming the figures before the committee sees them.
How we set it up
Free automation audit
We review your research, finance and reporting processes to identify where Financial Datasets data would save the most time. You leave with a clear list of workflows worth automating and a realistic estimate of effort.
Secure connection with an API key
We connect Claude to Financial Datasets using the API key sign-in method. The key is stored in your secure secrets manager, scoped to the minimum access needed and rotated on your schedule.
Workflow design and approvals
We design the end-to-end workflow across Financial Datasets and your other systems, such as Microsoft 365, your CRM or ERP. Actions that publish or change records are set to require human approval.
Testing against real cases
We test the workflow against past reporting periods and known results, checking accuracy, handling of missing data and the quality of Claude's written output before anything goes live.
Launch, monitoring and training
We launch with audit logs and monitoring in place, then train your analysts and finance staff on how to use the workflow, review outputs and escalate issues.
Who benefits
- Research analysts
- Spend less time gathering and reformatting figures and more time on interpretation and client-ready insight.
- Finance and reporting managers
- Produce consistent packs faster, with sources attached to every number for easier review.
- Credit and risk officers
- Apply the same ratio analysis across many borrowers and spot missing or unusual data sooner.
- IT and data governance leads
- Control access through a single scoped API key, with logs showing what data was requested and by whom.
Security and control
- Use a dedicated API key with the minimum access required, stored in a secrets manager and rotated regularly.
- Require a named person to approve any output that is published, shared externally or written into another system.
- Keep audit logs of queries and results so figures can be traced back to their source.
- Validate calculated ratios against a sample of manually checked figures before relying on them.
- Treat AI-generated commentary as a draft that must be reviewed for accuracy and suitability before use.
For teams in the US, UK, India and the Middle East
Organisations in the United States and the United Kingdom can use this workflow within their existing financial governance and data protection frameworks, including UK GDPR where personal data is involved. In India, the Digital Personal Data Protection Act, 2023 applies to personal data handling, and the hosting region can be chosen accordingly. For organisations in the UAE and Saudi Arabia, local data protection laws shape where data may be stored and processed. Hosting region is selected during design to meet these requirements.
Learn more about Claude and MCP
Anthropic's AI model and assistant.
Secure links between Claude and business tools.
How engineers build and change software with Claude.
Hosted agents that run multi-step work.
The open standard Claude uses to connect to tools.
Frequently asked questions
What does the Financial Datasets MCP server do?
The MCP server acts as a secure bridge between Claude and Financial Datasets. It lets Claude request company fundamentals, financial statements, SEC filings, market time series and macroeconomic data using natural language, and returns the results in a form Claude can summarise or calculate with. It only exposes the data types you approve during setup.
Is it secure to connect Claude to Financial Datasets?
Security depends on the design. We connect using your API key, store it in a secrets manager, limit access to what the workflow needs and log every request. Outputs that leave the workflow can be set to require human approval, so no consequential action happens without a person's sign-off.
What can Claude do with Financial Datasets once connected?
Typically, Claude can look up company fundamentals, retrieve SEC filings, query market data series, compute financial ratios and produce summaries or tables from the results. Its scope is defined during setup, so you decide which datasets and actions are available.
How long does setup take?
A focused single workflow is often connected and tested within a few weeks, following the free automation audit. Larger projects that involve several systems or custom applications take longer. We confirm a realistic timeline once we understand your processes.
What plan or permissions do we need?
You need an active Financial Datasets account that can issue an API key, with access to the datasets your workflow requires. Your data subscription level determines which datasets are available, so we confirm this during the audit before design begins.