Campinas Open Data MCP. Query city data and resource metadata instantly.
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Campinas Open Data MCP Server accesses public data from the city of Campinas, Brazil. Use your agent to search, filter, and retrieve metadata for city datasets, organizational contacts, and public resources.
You can find everything from health data packages to finance records using natural language queries.
What your AI agents can do
Get package
Fetches the complete metadata for a single dataset package.
Get resource
Retrieves metadata for a specific data file or resource within a package.
List groups
Lists thematic categories (like Education or Health) that organize the datasets.
Search the entire catalog of available datasets using keywords like 'education' or 'finance' via the search_packages tool.
List every city department or organization that has uploaded public data using the list_organizations tool.
Get full metadata for any specific dataset package using get_package to understand its contents and structure.
Filter and browse datasets using thematic groups via list_groups or by general tags using list_tags.
Get the metadata and link for a specific file (CSV, PDF) within a dataset using the get_resource tool.
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Campinas Open Data MCP Server: 8 Tools for Public Data Access
Use these tools to search, categorize, and get metadata for datasets, resources, and organizations across the Campinas Open Data Portal.
019e383aget package
Fetches the complete metadata for a single dataset package.
019e383aget resource
Retrieves metadata for a specific data file or resource within a package.
019e383alist groups
Lists thematic categories (like Education or Health) that organize the datasets.
019e383alist organizations
Lists all city departments or organizations that provide data to the portal.
019e383alist packages
Lists the names of all available datasets in the portal.
019e383alist tags
Lists all keywords and tags used across the entire data portal.
019e383asearch packages
Searches the catalog for datasets matching specific keywords or criteria.
019e383asearch resources
Searches for specific data files based on fields or names.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on every call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Campinas Open Data, then connect any of our 4,700+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,700+ others, all in one place
- Add new capabilities to your AI anytime you want
- Every connection is secured and compliant automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog every week
What you can do with this MCP connector
Your agent hooks into the Campinas Open Data Portal, giving you direct access to the city's public datasets. You can use natural language to search, filter, and pull metadata on everything from health records to finance reports. search_packages lets you search the whole catalog using keywords like 'education' or 'finance'.
You can list_organizations to see every city department that dumped public data. To check what's available by topic, you can list_groups for thematic categories or list_tags for general keywords. If you know a specific dataset, list_packages shows you all the available datasets in the portal. To dig into a dataset's structure, you use get_package to fetch the complete metadata.
For a specific file or resource inside a package, get_resource retrieves its metadata and link. Finally, search_resources lets you look for specific data files by field or name.
How Campinas Open Data MCP Works
- 1 Subscribe to the Campinas Open Data server, and provide your API Key if the data is restricted.
- 2 Tell your AI agent what you need. For example: 'List all organizations related to health data.'
- 3 The agent executes the appropriate tool (e.g.,
list_organizations) and returns a structured list of data providers, which you can then follow up on.
The bottom line is, you query the city data using natural conversation; the server handles the complex API calls behind the scenes.
Who Is Campinas Open Data MCP For?
Researchers, policy analysts, and journalists need this. If your job involves tracking public spending, comparing city metrics, or building academic models based on public data, this is for you. It cuts out the painful process of navigating dozens of separate government websites.
Uses search_packages to compare educational metrics (e.g., 'Escolas Municipais') against health metrics to identify resource gaps across different city regions.
Inspecting data schemas and file structures using get_resource and get_package so they know exactly how to ingest the data without manual cleanup.
Running list_organizations to build a list of every entity that contributes data, then using search_packages to track public spending or resource allocation by that entity.
What Changes When You Connect
- Stop clicking through directory trees. Use
search_packagesto find datasets related to 'Saúde' or 'Educação' instantly, rather than browsing through dozens of folders. - Build a data map of the city. Run
list_organizationsto get a definitive list of every department providing data, which is critical for understanding data coverage. - Understand the data schema before you download it.
get_packagegives you the full metadata, so you know exactly what fields to expect in the CSV. - Filter data by topic or keyword. Instead of searching everything, use
list_groupsto browse datasets by thematic areas like 'Finance' or 'Transport'. - Pinpoint the exact file you need. If you know the resource name,
search_resourcespulls the specific file metadata, bypassing the entire dataset wrapper. - Get a bird's-eye view of the catalog. Use
list_tagsto see all available keywords across the entire portal, helping you spot related data you didn't know existed.
Real-World Use Cases
Tracking Educational Spending
A policy analyst needs to compare spending on different school types. They ask their agent to use list_organizations to identify the relevant department, then search_packages for 'Educação' data, and finally get_package to confirm which metrics (like student-to-teacher ratio) are available in the dataset.
Finding Specific Financial Records
A journalist needs a file on last year's budget for a specific quarter. They run search_resources with the quarter and 'Financeiro' keywords, which bypasses browsing the entire dataset until the agent returns the direct metadata link.
Mapping Data Coverage
A developer wants to know if the city tracks water consumption data. They first run list_tags to see if 'Água' exists, then list_groups to see if there's a 'Saneamento' group, ensuring they don't waste time on irrelevant searches.
Assessing Public Health Data Availability
A researcher asks for all available health data. The agent uses list_organizations to identify the 'Secretaria Municipal de Saúde' and then uses search_packages to pull all related datasets, consolidating the scope of the research.
The Tradeoffs
Searching by partial name
Manually typing 'vagas' into a general search field and getting hundreds of results, forcing you to click through irrelevant packages and resources just to find the one dataset you need.
→
Use the search_packages tool and specify the exact criteria, like 'vagas em creches'. This narrows the search to only relevant datasets, saving clicks and time.
Ignoring data categorization
Trying to find all transport data by manually checking every department's website, which is slow, disorganized, and often results in missing links.
→
First, use list_groups to identify the 'Transporte' group. Then, use search_packages within that group to find all relevant datasets from every contributing organization.
Confusing packages and resources
Assuming that finding a dataset package name is the same as getting the actual data file. You get the name, but you still have to hunt down the right CSV link.
→
Use get_package to see the full metadata for the dataset, then use get_resource to pull the specific file link and its structure.
When It Fits, When It Doesn't
Use this server if your primary need is data discovery and metadata retrieval from a known public source. You need to know what data exists and who owns it before you can write any code or run any analysis. Use list_organizations and list_groups first to map the scope.
Don't use this if you need to actually download or process the data. The server only provides metadata and links; you still need a separate data pipeline tool (like a database connector) to pull the actual content. If you're looking for internal, private company data, this won't help—you need a private data warehouse connection instead.
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Campinas Open Data Portal. 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 8 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Available Capabilities
Sifting through city data used to mean clicking through endless directories.
Today, finding a dataset requires a deep dive: you visit the portal, click the 'Health' category, then click 'Dataset List', then click 'Department X', and finally, you're presented with a list of packages, most of which are irrelevant. You waste time clicking through metadata pages just to find the name of the right file.
With the Campinas Open Data MCP Server, you just tell your agent what you need. You prompt it to 'Search for education data from the city.' The agent uses `search_packages` and instantly returns the metadata for the correct dataset, skipping all the folder clicking.
Campinas Open Data MCP Server: Accessing Public Records
You no longer have to manually check every department's website. The server runs `list_organizations` and gives you a clean, consolidated list of all data providers. Then, you use `search_packages` to run a query across all of them simultaneously.
It’s a single point of access. The city's data, from every department, is exposed through one structured API. No more jumping between siloed government sites.
Common Questions About Campinas Open Data MCP
How do I use the `search_packages` tool on the Campinas Open Data MCP Server? +
You tell your agent to search for the topic you need, like 'Educação'. The agent runs search_packages and returns a list of matching dataset names and brief descriptions.
What is the difference between `list_organizations` and `list_packages`? +
list_organizations tells you who provides the data (the department name). list_packages tells you what the datasets are (the dataset name). You often need both to map the source and the content.
Can I use `get_resource` to get the data itself? +
No, get_resource only retrieves the metadata and the direct link to the file. You still have to use that link in your own code to download or process the actual CSV or PDF data.
Does `list_tags` include all possible keywords? +
Yes, list_tags shows every tag applied across the entire portal. This is a great way to find related datasets you might not have thought to search for.
How does `get_package` help me understand a dataset's scope? +
It provides the full metadata for a specific dataset. This metadata shows the dataset's last update date, the types of resources it includes (like CSV or PDF), and a description of what data it covers.
What criteria can I use when calling `search_packages`? +
You can search for datasets using keywords. The system processes these keywords against the dataset's title, description, and available tags to find matches.
Is there a limit on how many items I can retrieve using `list_tags`? +
The tool fetches all active tags used across the portal. If the total number of tags exceeds the API's limit, the response will include pagination instructions to get the rest.
If I encounter an API key error, how do I fix it when using any tool? +
You need to verify your API key and ensure it's correctly provided in the server's configuration. If the data is public, the key might be optional, but restricted data requires proper authentication.
How can I search for datasets related to a specific topic like 'Health'? +
You can use the search_packages tool with a query string. For example, searching for 'saude' will return all datasets categorized under health in the Campinas portal.
Can I see which city departments are publishing data? +
Yes! Use the list_organizations tool to get a complete list of all city departments and entities that contribute to the Open Data Portal.
How do I get the download link for a specific data file? +
Use the get_resource tool with the specific Resource ID. It will return the metadata, including the URL to download the file (CSV, PDF, etc.).
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.
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