Best Financial MCP Servers for Claude & ChatGPT (2026)

The short answer

An AI agent that analyzes stocks from web search alone is not reliable enough to inform a money decision. A financial data MCP server fixes that, and the right one depends on which kind of data your question needs. For most individual investors and small teams, a sensible setup is one self-serve research server for financials, narrative research and company knowledge (Distilla), plus one market-data server for live prices (Massive, Alpha Vantage or EODHD). Funds that already hold licences can add FactSet, S&P Capital IQ, AlphaSense or Daloopa.

Underneath that sit four kinds of data, and two access tiers:

•           Market data (prices, volumes): commoditized. Massive, Alpha Vantage, EODHD, FMP and Finnhub all cover it.

•           Financials and other numbers (statements, segments, KPIs): FactSet, S&P Capital IQ and Daloopa at the high end; FMP, Financial Datasets and Distilla at the self-serve end.

•           Qualitative and narrative data (filings, transcripts, broker research, podcasts, events): AlphaSense at the high end; Distilla is the broadest self-serve option we found.

•           Company knowledge (what drives each business, and why the stock moved): a new layer. Distilla is the only server we found that offers it, as of 6 October 2026.

Enterprise servers (Capital IQ, FactSet, AlphaSense) are sold to funds through sales teams. A newer self-serve tier (FMP, Finnhub, Financial Datasets, Massive, Alpha Vantage, EODHD, Distilla) is built for individual investors, small teams and analysts. Distilla sits in both: the same data layer serves large funds through an enterprise product and individual investors through self-serve plans. Most people end up connecting two or three servers.

Why your agent needs a data MCP server

MCP, the Model Context Protocol, is the open standard that lets an AI assistant call tools outside itself. A financial data MCP server puts market, company or research data behind those tools. In Claude it is added as a connector; ChatGPT, Cursor and agents you build yourself work the same way.

Without a data connection, an agent falls back on training data and web search. For stock analysis, that has four problems:

•           Biased. Search results are dominated by whoever publishes the most, optimizes best for search, or has something to sell. Promotional and one-sided content ranks well.

•           Outdated and incomplete. Training data stops at a cutoff. Search returns whatever pages happen to be indexed and readable: no paywalled research, no full filing history, and little on non-US companies.

•           Sometimes simply wrong. Web pages repeat each other’s errors, mix up share classes and fiscal periods, and quote figures without a source or date.

•           Inconsistent. Sources conflict, so the same question can produce different answers on different runs, depending on which pages the agent happened to open.

If you are relying on an agent’s analysis to put money to work, an answer that changes from run to run, or rests on a stale or incorrect number, is not acceptable. The fix is to give the agent a governed data source: dated, sourced and the same every time it asks. Next to the size of the positions most investors are deciding on, a data subscription is a small cost, and the return on it is avoiding decisions built on bad inputs. A connected server makes errors much less likely, but it does not make checking optional: ask the agent for a source and a date for every figure, and confirm the ones that matter.

Two tiers of financial data MCP servers

Financial data MCP servers today fall into two groups.

The self-serve tier is the newer one, and it exists to bring data that used to be reserved for funds within reach of prosumers and analysts. It matters because financial data is becoming a long-tail product. As information and financial knowledge become easier to get, more sophisticated individuals and small teams are taking control of their own investing, and they need the same quality of inputs a fund gets. Self-serve vendors differ widely in which kinds of data they cover, so the next section matters more than the tier.

Four layers of financial data

Almost every question an investor asks an agent falls into one of four layers.

A dash means we could not confirm the capability on the vendor’s own pages; it does not necessarily mean the vendor lacks it. Finnhub’s MCP servers are community-built wrappers around its API.

Layer 1: Market data (prices, volumes, bars)

For questions like “What did NVDA close at each day last month?” or “Plot AAPL’s 50-day moving average.”

This layer is largely commoditized. The raw figures can be had from free sources such as Yahoo Finance, and every vendor above includes them. Choose on what else you need and on intraday depth, not on price data alone.

Distilla also has daily prices, volume, market cap and sell-side target prices for the companies it covers, but no intraday or real-time data. If you need live quotes, pair it with one of the servers above.

Layer 2: Financials and other numbers

For questions like “Compare gross margin for MSFT, GOOGL and AMZN over the last eight quarters” or “How fast is Costco’s membership fee revenue growing?”

Statements and segment data have traditionally been compiled by people, which is why Capital IQ and FactSet are strong here and why they cost what they do. AI-native extraction now pulls the same numbers, and more, straight from filings. Financial Datasets and Distilla both use AI to extract segment numbers from filings, overlapping with what Daloopa sells to funds. Distilla extracts further, including industry-specific metrics based on industry templates (examples: ARR, customer concentration, RevPAR), as part of how it indexes each company.

For a model that must tie out to the filing line by line, Daloopa’s source-linked KPIs remain the specialist choice.

Layer 3: Qualitative and narrative data

For questions like “What did management say about pricing on the last three calls?” or “What is the sell-side debating on this stock?”

This layer is newer, and it is what lets an agent reason about fundamentals and sentiment rather than just retrieve numbers. AlphaSense sells filings and research to funds. FMP and Finnhub offer transcripts and filings. Distilla indexes the widest mix of narrative source types we found in a self-serve product: filings, earnings-call transcripts, sell-side research summaries, investor podcast summaries and company events.

Distilla is not a replacement for AlphaSense if your process depends on expert-call transcripts, full broker reports or searching internal documents.

Layer 4: Company knowledge

For questions like “Why did Adobe fall after earnings?” or “What actually drives this company’s earnings, and who are its peers?”

This layer is also new. It compresses facts about a company into a standard, consistent understanding with little need for opinion: what drives the business, which products and peers matter, which events happened and when, and how each price move links to those events and to sentiment over time. Distilla is the only server we found that offers it; none of the other vendors’ documentation, as of 6 October 2026, describes a comparable layer.

The first three layers leave a gap here. Take Adobe’s fiscal Q3 2026 report on 10 September. A market-data server will show you the stock trading lower after hours. A financials server will show you that revenue and EPS both beat. A narrative server will give you the transcript. None of them links the sell-off to the events behind it, or separates the reaction to the results from later, unrelated news. That is what price attribution does.

Geography: you don’t need the whole world

Coverage maps look impressive, but most investors do not need most of them. By our count, fewer than 3,000 listed companies across the US, Japan, Korea, Hong Kong and Taiwan combine a market capitalization above $2B with daily liquidity above $20M, which is roughly the set that is open to international investors in size. Wall Street brokers generally cover not much more than this set, so analyst research, estimates and call transcripts exist for these names and thin out below them.

Three practical consequences:

•           Large and mid caps in the main markets are the core need. A server that covers this set well is more useful than one that lists 150,000 tickers with shallow data.

•           For small caps, go to the filings. Data vendors and web content are thin on small companies, so the primary documents are usually the best source.

•           Skip markets you cannot invest in. If you have no access to China or India, there is no point paying for coverage of them.

On geography, the enterprise vendors cover the most, but at fund-level prices. FMP’s full global coverage sits on its top plan, and Financial Datasets covers US stocks only, by its own documentation. Among self-serve vendors, Distilla is the one that combines the financials, narrative and company-knowledge layers across the US, Japan, Hong Kong, Korea and China A-shares, with sell-side and podcast summaries extending beyond that core universe.

How to choose a financial MCP server

Start with the layer your most frequent question needs.

•           Price, charts or returns: a market-data server: Massive, Alpha Vantage, EODHD, FMP or Finnhub.

•           Reported numbers only: a financials server. Financial Datasets and FMP are the easiest to sign up for yourself; Daloopa, S&P Global and FactSet make sense if your firm already licenses them.

•           What management said, what the street thinks, how an issuer is rated: AlphaSense, Morningstar, LSEG or Moody’s if you have a licence; Distilla if you want it self-serve.

•           Why a stock moved, what drives the business, and the bull and bear cases: Distilla.

Three practical checks come after that.

1.         Can you get access today? FactSet, S&P Global, LSEG, Morningstar, Moody’s and AlphaSense need an existing licence or a sales conversation. Massive, Alpha Vantage, EODHD, Financial Datasets, FMP, Finnhub and Distilla let you start on your own, and Distilla has a free plan.

2.         Does it cover your market? Several of these servers are built around US stocks. Check coverage for every market you actually invest in.

3.         Does it work on your plan? Most servers here support both Claude and ChatGPT, but plan requirements differ, so check the vendor page for the plan you are on.

You don’t have to pick just one

Claude and ChatGPT can both hold several connectors at once, and the model decides which tool to call for each part of a question. For an individual investor or a small fund, a sensible starting stack is Distilla for financials, narrative and company knowledge, plus one market-data server for live and intraday prices. Add a licensed enterprise source such as FactSet or S&P Global if your firm already pays for it.

Here is how that plays out on a question like “Adobe sold off after earnings. Why, and is it cheap against its own history?” Distilla supplies the explanation of the move with dates and sources, along with statements, consensus and valuation multiples. A market-data server supplies any intraday price history you need on top.

It helps to spell out the division of labour in your prompt or project instructions, for example: “Use Distilla for why questions, estimates and statements, and Alpha Vantage for intraday prices.”

Distilla is built for agentic investing workflows that research before they act: it researches, and it never places orders. If your agent will also place orders, pair it with a brokerage MCP, keep research and execution in separate connectors, and keep a human approving every order.

Distilla in depth

Distilla brings institutional rigor to individual investors and small teams. It is the fundamental research layer for AI agents: an MCP server and HTTP API that tells your agent why stocks move, what management said, what the sell-side and podcast guests are debating, and what drives each business.

The same underlying data powers an enterprise product, including an agent, used by some of the world’s top funds, from firms managing hundreds of millions of dollars to firms managing tens of billions. The data layer is also packaged as a self-serve product, so an individual investor or a small team works from the same dated, sourced facts, not a thinner or lesser version. The difference between the two is access and scale, not the quality of the underlying research. It works with Claude, ChatGPT, Claude Code, Cursor, WorkBuddy, Doubao and your own agents, and a no-AI web app (Distilla Lite) uses the same research. It is read-only, and every fact is dated and traceable to its source document.

Core coverage: the most-followed companies in the US, Japan, Hong Kong, Korea and China A-shares; sell-side and podcast summaries extend beyond the core universe. Access: self-serve with a free plan, and paid plans from $9.90/month; an enterprise product for funds. Not included: intraday data, options, full broker reports, expert-call transcripts, trading.

Three ways to use Distilla

•           Distilla MCP, for analysts and PMs: connect it to Claude, ChatGPT, Claude Code, Cursor, WorkBuddy or Doubao and ask in plain English.

•           Tools API, for developers and quants: the same tools over HTTP (POST /tools/{name}) for dashboards, screens, backtests and scheduled jobs, with identical JSON.

•           Distilla Lite, for browser users with no AI assistant: one-page tearsheets, earnings history, every big move with its reason, valuation ranges, peers and the research and podcast library.

Where Distilla is not the right tool

Distilla has no intraday or real-time data, no options data, no expert-call transcripts, no full broker reports and no trading. It returns summaries of company events, sell-side reports and podcasts in json, and its explanations are written by a language model from linked events. For live quotes or tickers outside its core coverage, pair it with a market-data server such as Massive, Alpha Vantage, EODHD or just yahoo finance.

FAQ

What is Distilla?

Distilla is the fundamental research layer for AI agents: an MCP server and HTTP API that gives Claude, ChatGPT and your own agents financial statements, consensus estimates, filings, transcripts, 180K+ sell-side research summaries, 11K+ investor podcast episodes, company events, business drivers and 438K+ explained price moves, with every fact dated and sourced. It brings institutional rigor to individual investors and small teams, and the same data powers an enterprise product used by funds. Core coverage is the US, Japan, Hong Kong, Korea and China A-shares.

Why do I need a financial data MCP server?

Without one, an AI agent answers from training data and web search, which can be biased, outdated, incomplete or wrong, and can give different answers on different runs because sources conflict. A data MCP server gives the agent dated, sourced data that is the same every time it asks. That matters when you are making decisions with real money.

What is the best financial MCP server for Claude?

It depends on the layer. For prices, look at Massive, Alpha Vantage, EODHD, FMP or Finnhub. For audited statements at a firm that already licenses a data terminal, look at FactSet, S&P Global or Daloopa. For one self-serve connector that covers financials, narrative research and company knowledge across the US, Japan, Hong Kong, Korea and China A-shares, Distilla is built for that. Many users run Distilla alongside a market-data server.

What is the difference between enterprise and self-serve financial data MCP servers?

Enterprise servers (Capital IQ, FactSet, AlphaSense and similar) are sold to funds through sales teams, usually at fund-level prices. Self-serve servers (FMP, Finnhub, Financial Datasets, Massive, Alpha Vantage, EODHD, Distilla) can be started online with a free tier, trial or monthly plan, and suit individual investors, small teams and analysts. Coverage varies much more among the self-serve vendors. Distilla offers both: an enterprise product for funds and a self-serve plan built on the same data.

What is the best stock research MCP server?

It depends on the source you need. For equity research built on filings, transcripts and analyst content at a firm with a licence, look at AlphaSense or S&P Global (Kensho). Distilla summarizes 180K+ sell-side reports and 11K+ investor podcast episodes alongside filings, earnings-call facts and 438K+ explained price moves, and individual investors can start on a free plan, with paid plans from $9.90/month.

What is the best earnings call transcript MCP server?

Alpha Vantage, FMP (on its top plan), Finnhub, S&P Global and Distilla all list transcripts. Distilla also extracts structured facts from calls (segments, guidance, KPIs and topic changes) so an agent can compare what management said across quarters.

What is the best MCP server for Japanese, Hong Kong, Korean or Chinese stocks?

Many financial MCP servers focus on US tickers. Distilla’s core coverage is the most-followed companies in the US, Japan, Hong Kong, Korea and China A-shares, with company events, price-move explanations and research summaries for each market, and it handles local tickers, currencies and fiscal-year end dates.

Do financial MCP servers work with ChatGPT?

Yes. Most servers in this guide list support for both Claude and ChatGPT, including Alpha Vantage, Financial Datasets, Daloopa, Morningstar, S&P Global and Distilla. Which ChatGPT plans are supported varies by vendor.

Are there free financial MCP servers?

A few. Alpha Vantage allows 25 requests a day on a free key, EODHD allows 20 calls a day on its free plan, FMP’s free plan allows 250 calls a day, and a free Massive Basic account can connect. Distilla's free plan includes 100 tool calls a month. The enterprise servers all require a licence.

How much does Distilla cost?

Lookout is free, with 100 tool calls a month and no card required. Scout is $9.90/month for 200 tool calls a week, Explorer is $29/month for 1,000 a week and Navigator is $249/month for 10,000 a week. Paid plans come with a 7-day free trial and a 20% saving on yearly billing. Fleet is custom-priced for institutions (e.g. multi-billion funds building their own data lake / strategy).

Can I use Distilla without Claude or ChatGPT?

Yes. The Tools API serves the same data over HTTP for scripts, dashboards and backtests, and Distilla Lite is a browser app with tearsheets, earnings history, explained price moves, valuation ranges, peers and the research library, with no AI assistant required.

Can I connect more than one MCP server at the same time?

Yes. Add each one as a separate connector. The model will choose between them, and you can steer that choice with instructions.

Can a financial MCP server place trades?

Not the ones in this guide. They are data servers. Distilla, EODHD and Daloopa all state that their servers are read-only, and Distilla never places orders.

How do I know the answer is right?

Ask the model to give a source and a date for every figure, then check the ones that matter against the original filing or transcript. A connected server makes errors much less likely, but it does not make checking optional. Distilla’s facts are point-in-time, dated and traceable to the source document.

Is Distilla only for individual investors?

No. Distilla brings institutional rigor to individual investors and small teams through self-serve plans, and the same data also powers an enterprise product, including an agent, used by funds managing from hundreds of millions to tens of billions of dollars. Funds that want the enterprise product can contact Distilla; individuals and small teams can start on the free plan.

Is this investment advice?

No. Distilla is a research tool, not investment advice. This guide compares data tools and does not recommend any security.

About Distilla

Distilla brings institutional rigor to individual investors and small teams. It is the fundamental research layer for AI agents: why stocks move, not just where. The same data powers an enterprise product, including an agent, used by some of the world’s top funds, and is also packaged as a self-serve product so individuals can work from the same facts. It is an MCP server and HTTP API that gives Claude, ChatGPT and your own agents quantitative data, qualitative research and structured company knowledge in one queryable, read-only layer.

•           Quantitative: financial statements, analyst consensus, valuation history and company metrics, including AI-extracted segments and industry-specific KPIs.

•           Qualitative: earnings-call and filing commentary, 180K+ sell-side research summaries and 11K+ investor podcast episodes.

•           Company intelligence: 1,000+ company knowledge topics, business drivers updated quarterly, company events (about 50,000 added weekly), products, peers and sector relationships, and 438K+ explained price moves of 3% or more.

Core coverage is the most-followed companies in the US, Japan, Hong Kong, Korea and China A-shares; sell-side and podcast summaries extend beyond the core universe. Read-only MCP server at https://api.distilla.ai/mcp, with the same lookups over an HTTP API. Works with Claude, ChatGPT, Claude Code, Cursor, WorkBuddy and Doubao. Self-serve: free plan, with paid plans from $9.90/month. Enterprise: contact Distilla. Distilla is a research tool, not investment advice. Figures are as of 7 October 2026.