CFPB Complaints MCP. Track systemic financial disputes in millions of records.
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CFPB Complaints: Access the Consumer Financial Protection Bureau's database of over 13.8 million consumer complaints. You can search by company, state, product (like mortgages or credit cards), or specific issue type (like incorrect information).
This tool gives you the raw data to track financial company behavior and see common consumer pain points.
What your AI agents can do
Get company complaints
Retrieves complaint details (products, issues, states, dates, company responses) for a specified company.
Get complaint
Gets full details for one specific complaint ID, including the consumer narrative and company response.
Get complaints by issue
Retrieves complaints filtered by common issue types like 'Incorrect information' or 'Problem with a purchase'.
Retrieve a list of complaints, including products, issues, states, and dates, associated with a given financial company.
Get a list of complaints, including products, companies, issues, and dates, originating from a specific US state.
Get complaints for specific financial products, such as 'Mortgage' or 'Debt collection'.
Get complaints filtered by common issue types, like 'Incorrect information' or 'Problem with a purchase'.
Fetch the full details of a single complaint using its unique ID, including the consumer's narrative and company response.
Retrieve the most recently filed consumer complaints to track immediate activity and emerging issues.
Calculate statistical counts across the database without needing to pull individual complaint records.
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CFPB Complaints: 9 Tools for Financial Data Analysis
Access and filter consumer complaints from the CFPB database across products, companies, states, and issues using these nine specialized tools.
019d8423get company complaints
Retrieves complaint details (products, issues, states, dates, company responses) for a specified company.
019d8423get complaint
Gets full details for one specific complaint ID, including the consumer narrative and company response.
019d8423get complaints by issue
Retrieves complaints filtered by common issue types like 'Incorrect information' or 'Problem with a purchase'.
019d8423get complaints by product
Retrieves complaints filtered by financial product types like 'Mortgage' or 'Credit card'.
019d8423get complaints by state
Retrieves complaints from a specific US state, listing associated products, companies, and issues.
019d8423get complaints stats
Generates quick statistical counts of complaints across the database without fetching full records.
019d8423get complaints with narrative
Retrieves complaints that include the full consumer narrative, allowing review of detailed personal accounts.
019d8423get recent complaints
Gets the most recently filed consumer complaints to track immediate filing trends.
019d8423search complaints
Searches the entire database of financial complaints using filters for product, company, state, issue, and date range.
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What you can do with this MCP connector
You've got direct access to the Consumer Financial Protection Bureau's database, tracking over 13.8 million consumer complaints. Your AI client lets you dive deep into financial misconduct. You don't need an API key; the data's public, and you'll use this to track what's going down with financial companies.
To check out a specific company, you'll use get_company_complaints to pull a list of their complaints, giving you the products, issues, states, and dates involved. If you wanna see what's happening in a particular state, get_complaints_by_state lists complaints from that US state, showing you the products, companies, and issues involved there.
You can also focus on a single product type, running get_complaints_by_product for things like 'Mortgage' or 'Debt collection'. Wanna know about a specific problem, get_complaints_by_issue pulls complaints filtered by issue types like 'Incorrect information' or 'Problem with a purchase'.
If you've got a complaint ID, get_complaint gets you the full details for that one complaint, including the consumer's full story and the company's response. You can pull complaints that include the full consumer narrative using get_complaints_with_narrative for detailed personal accounts. To track what's happening right now, get_recent_complaints grabs the most recently filed complaints, so you can track immediate filing trends.
You can search the entire database using search_complaints, filtering by product, company, state, issue, and a date range. Need a quick overview? get_complaints_stats generates statistical counts across the database without pulling full records.
How CFPB Complaints MCP Works
- 1 Start by connecting your AI client to the CFPB Complaints MCP Server.
- 2 Ask your agent to perform a focused query—for example, 'Show me all complaints against Bank X in California about mortgages.'
- 3 The agent runs the necessary tools, compiling data points like product, issue, state, and company response for you to review.
The bottom line is you get structured, filterable access to millions of consumer complaints without needing to write complex database queries.
Who Is CFPB Complaints MCP For?
Anyone who needs to know if a financial company is behaving badly. This is for the compliance officer who has to write reports on regulatory risk, the researcher mapping industry failures, or the journalist investigating corporate misconduct. Stop guessing about industry risk—get the actual complaint data.
Runs checks on specific companies or product lines to identify high-risk areas before an audit or regulatory filing.
Analyzes complaint patterns across multiple states or products to identify systemic weaknesses in an industry sector.
Gathers specific complaint data points for stories about financial misconduct or regulatory lapses.
What Changes When You Connect
- See exactly what companies are doing wrong. Use
get_company_complaintsto pull all complaints against a single entity, instantly showing regulatory risk profiles. - Identify product weak spots across the nation. Run
get_complaints_by_productto see complaint volumes for 'Student loan' vs. 'Credit card' and spot industry-wide failures. - Analyze regional risk patterns. Use
get_complaints_by_stateto compare complaint distribution between states, finding where the most pressure points are. - Understand the why behind the numbers. Use
get_complaints_with_narrativeto read detailed consumer accounts, moving beyond just metadata counts. - Quickly gauge overall trends. Run
get_complaints_statsto get immediate complaint counts, letting you assess the magnitude of a problem without pulling massive datasets. - Pinpoint emerging issues. Use
get_recent_complaintsto track the latest filings, helping you react to a problem before it becomes a major headline.
Real-World Use Cases
Tracking a competitor's reputation
A competitive intelligence analyst needs to know how Bank B is performing compared to Bank A. They use search_complaints to run a comparison, filtering both by 'Mortgage' and a specific date range. The agent returns a side-by-side view of complaint volumes and top issues for both banks, allowing the analyst to report on relative market risk.
Investigating a specific consumer issue
A journalist is writing a piece on debt collection practices. They use get_complaints_by_issue to narrow the search to 'Attempts to collect debt not owed.' Then, they use get_complaints_with_narrative to pull 10 specific examples, gathering direct quotes and details for the story.
Analyzing state-level regulatory gaps
A policy researcher wants to see if consumer fraud is concentrated geographically. They use get_complaints_by_state for three specific states. The agent compiles the data, showing which products are generating the most complaints in each region, helping the researcher pinpoint where new state regulations are needed.
Deep dive on a single account
A paralegal needs to verify all records against one company. They first run get_company_complaints for that company. Then, if they find a suspicious complaint ID, they use get_complaint to pull the full, unedited details and company response for legal review.
The Tradeoffs
Using only basic keyword search
The user tries to search for 'bad customer service' in search_complaints and only gets results because the words 'bad' and 'customer' were used. This misses the core problem: systemic failure.
→
Don't just search keywords. Instead, use get_complaints_by_issue to filter by 'Incorrect information' and then combine that with get_complaints_by_product for 'Credit card'. This narrows the scope to the actual systemic failures.
Relying on raw numbers alone
The user runs get_complaints_stats and sees that 'Mortgage' is the top complaint category. They assume the issue is widespread, but don't know why the complaints are happening.
→
Get the volume, then get the cause. Use get_complaints_by_product for 'Mortgage', and immediately follow up by using get_complaints_by_issue to drill down to the most common cause, like 'Problem with a purchase'.
Skipping the narrative details
The user runs search_complaints and gets a list of 500 records with only metadata (Company X, Date Y). They stop there, missing the actual story and context.
→
Always check the narrative. After running a search, use get_complaints_with_narrative to pull a sample of records. This gives you the actual consumer voice and context needed for real analysis.
When It Fits, When It Doesn't
Use this server if your goal is to map out patterns of failure—you need to know why and where consumers are complaining, not just that they are complaining. If you need to know the total volume of complaints for a given category, start with get_complaints_stats. But if you need to understand the root cause, you must chain tools: use get_complaints_by_product to narrow the area, then get_complaints_by_issue to find the specific problem, and finally get_complaints_with_narrative to read the full story. Don't stop at the search results. Never rely on a single tool call when the problem is complex.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by CFPB Consumer Complaint Database. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Works with Claude, ChatGPT, Cursor, and more
The Model Context Protocol standardizes how applications expose capabilities to LLMs. Instead of operating in isolation, your AI gains direct access to external platforms, live data, and real-world actions through secure, standardized connections.
This server provides 9 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Tracking financial disputes shouldn't require reading a manual.
Today, finding out why a company is getting complaints means jumping between separate government websites, running manual filters, and downloading massive CSVs. You spend hours cross-referencing dates, products, and states, all while hoping you didn't miss a key data point or a critical narrative.
With this MCP server, you just talk to your agent. You ask, 'What are the top complaints about mortgages in California?' and it pulls the data from the CFPB database, giving you immediate, structured answers without the manual clicks or the headache of data formatting.
CFPB Complaints: Get the full story with `get_complaints_with_narrative`
Before, if you wanted to know the consumer's side of the story, you had to find the basic complaint record, then manually hunt for the detailed narrative text, which was often buried or incomplete.
Now, you ask for narratives directly. The agent retrieves the detailed consumer descriptions alongside the metadata, giving you the full context needed for deep reporting. You get the story, not just the data points.
Common Questions About CFPB Complaints MCP
How do I find complaints about a specific company using `get_company_complaints`? +
Just provide the company name to the tool. It returns a list of all complaints against that entity, showing the product, issue, state, and date for each one.
What is the best way to compare product failures across states? +
You should combine tools. Use get_complaints_by_product first to narrow the focus (e.g., 'Credit card'), and then use get_complaints_by_state to see how that product is performing in different regions.
Do I need an API key to use `search_complaints`? +
No, you don't. The data is open public domain, so you can use search_complaints directly through your AI client without worrying about keys.
Which tool should I use to get the total number of complaints? +
Use get_complaints_stats. This tool provides a quick count without retrieving the full details of every single complaint, which saves time and resources.
How do I read the full text of one complaint using `get_complaint`? +
Provide the specific complaint ID to get_complaint. This fetches the complete record, including the consumer's detailed narrative and the company's official response.
How can I check for complaint trends over time using `get_recent_complaints`? +
You use get_recent_complaints to track complaint trends. This tool provides the most recent filings, allowing you to see if complaint volume or specific issues are increasing or decreasing over time.
If I need a full breakdown of complaints for a specific product, should I use `get_complaints_by_product` or `search_complaints`? +
Use get_complaints_by_product for a focused list of complaints specific to one product type. If you need to filter that product list by state, date, or company name, then search_complaints is better.
What information does the `get_complaints_with_narrative` tool return? +
This tool returns complaints that include the full consumer narrative. This is crucial because the narrative provides the consumer's detailed, first-hand account of their experience, which is often more valuable than the basic metadata.
Do I need an API key? +
No! CFPB complaint data is completely free and open public domain. No authentication required.
What products are covered? +
Complaints cover: Debt collection, Mortgage, Credit card, Credit reporting, Student loan, Bank account, Payday loan, Money transfer, Prepaid card and many more.
Can I read consumer narratives? +
Yes! Use get_complaints_with_narrative to find complaints that include the consumer's detailed description of their experience.
How recent is the data? +
The database is updated daily with new complaints. Complaints are published after the company responds or after 15 days, whichever comes first.
Use it with your favorite AI tools
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