vCard Contacts Parser MCP. Structure messy contact exports into clean JSON data.
Gemini Works with every AI agent you already use
…and any MCP-compatible client
Just plug in your AI agents and start using Vinkius.
vCard Contacts Parser converts huge, messy iPhone and Android .vcf exports into clean, queryable JSON. Don't let raw contact files break your AI client or hallucinate data.
This tool processes thousands of contacts locally, stripping out binary noise (like profile pictures) and leaving you with structured fields: First Name, Last Name, Organization, Phone, Email.
What your AI agents can do
Parse kindle clippings
Pasting the raw text from a Kindle 'My Clippings.txt' file parses notes and bookmarks into structured JSON, grouping them by book.
The tool reads a raw .vcf file and outputs structured JSON containing names, organizations, phones, and emails.
It takes the plain text content from an Amazon Kindle 'My Clippings.txt' export and structures notes, bookmarks, and highlights by book title.
You can query the entire contact list to find specific individuals based on their job title or employer.
The tool structures extracted contact records into a clean, comma-separated value format ready for spreadsheets.
Ask AI about this MCP
Supported MCP Clients
OAuth 2.0 Compatible Gemini Waiting for input…
vCard Contacts Parser MCP Server: 1 Tool
Use the available tools to structure various exported files—from vCards to Kindle clippings—into machine-readable JSON data.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using vCard Contacts Parser on Vinkius019e38b4parse kindle clippings
Pasting the raw text from a Kindle 'My Clippings.txt' file parses notes and bookmarks into structured JSON, grouping them by book.
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 vCard Contacts Parser, then connect any of our 4,900+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 4,900+ 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
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by vcard-parser. 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.
VINKIUS INFRASTRUCTURE
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on every call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
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 1 capabilities that interface natively with Claude, ChatGPT, Cursor, and any MCP client. No middleware. No custom integration required.
Exported contact lists are messy. You know it.
You get a big `.vcf` file from your phone or CRM, right? It looks fine at first glance, but when you try to read it with an AI client, the model gets distracted by all the junk data—the base64 profile pictures, the old formatting tags. Suddenly, your context window is full of binary garbage instead of actual names and numbers.
With this MCP Server, you feed that mess into the parser first. It strips away the noise locally, leaving you only with structured JSON: Name, Phone, Email. Your agent gets clean data instantly. No hallucination, no wasted tokens.
vCard Contacts Parser MCP Server
You eliminate the manual process of opening a file, scrolling through hundreds of entries, and mentally cross-referencing which column holds the email vs. the phone number. You don't have to copy anything; your agent handles it.
The result is predictable JSON output every time. Your AI client treats the data like it was built for an API, not just dumped from a mobile operating system.
What you can do with this MCP connector
You know the drill when you pull contact data off a phone—you get a massive, messy .vcf file. These things are full of old BEGIN:VCARD junk and useless binary garbage, like base64-encoded profile pics. If your AI client reads that raw mess, it'll choke on context window limits or, worse, start hallucinating phone numbers and emails out of thin air.
This MCP is a dedicated contact intelligence engine. It runs 100% locally, meaning your data never leaves your machine. It strips away all the binary noise and converts the raw vCard format into beautiful, easily queryable JSON that your AI client actually understands. When you use parse_vcard, it takes that sprawling .vcf file and gives you structured fields: First Name, Last Name, Organization, Phone Number, and Email Address.
Need to find someone specific? You can query the entire contact list using the system's search functions; just tell your agent to locate individuals based on their job title or company. The tool doesn't just parse names; it reads every field, accurately differentiating a person’s given name from their family name and pulling out corporate affiliations so you get clean data sets.
If contacts aren't what you need, we got your back for Amazon highlights too. When you use parse_kindle_clippings, you feed it the plain text dump from an Amazon Kindle 'My Clippings.txt' export. The tool doesn’t just dump that text; it structures notes, bookmarks, and highlights into clean JSON objects, grouping them logically by book title so you know exactly what came from where.
Processing data for a spreadsheet? When the job is done, use the built-in formatting to get your extracted contact records or Kindle clippings formatted for CSV export. This gives you a crisp, comma-separated value file ready to paste straight into any major spreadsheet program. You're not just parsing; you're preparing actionable intelligence.
This server handles huge volumes—it processes vCard files containing thousands of contacts instantly. It keeps everything local for maximum privacy and zero hallucination risk. It ensures perfect extraction of country codes, complex email formats, and specific job titles every single time.
019e38b5-0fe4-708e-bb26-53d399d772bd 
How vCard Contacts Parser MCP Works
- 1 You point your AI client at the raw file (either a
.vcfexport or Kindle clippings text). - 2 The parser runs locally, stripping away all unnecessary binary data and parsing the specific records.
- 3 Your agent receives a clean JSON array, ready for direct use in prompts: e.g., 'List emails for people at Company X'.
The bottom line is you get structured, usable data without ever uploading your private files to an external server.
Who Is vCard Contacts Parser MCP For?
Data analysts dealing with messy CRM exports. Operations engineers who need quick contact lists for internal comms. Sales reps who constantly deal with contacts from various sources (phone, email, cloud). If you spend time cleaning up spreadsheets before using data, this is for you.
Uses the tool to normalize contact lists from mixed sources (vCard and Kindle) into a consistent JSON schema for database insertion.
Requires quick, accurate phone numbers or department roles for internal team communication without manual data entry.
Processes large vCard exports to quickly filter and identify contacts who work at target companies.
What Changes When You Connect
- Stop context window overflow. Instead of sending a massive, raw
.vcffile to your agent—which will chew up tokens and hallucinate—you feed the parser. It returns only clean JSON structured with fields like 'Email' and 'Phone'. - Maintain absolute privacy. Since the parsing happens locally on your machine, your entire address book never leaves your device or hits a third-party server. That's essential for sensitive data.
- Process massive files easily. Don't worry about file size. The tool handles VCF exports containing thousands of contacts without breaking or slowing down your workflow.
- Filter contacts by specific criteria. Your agent can run direct queries, like 'Find the contact who works at Google,' and get a precise list instead of having to search through every single record manually.
- Use it for notes too. While built for vCard data, the tool includes
parse_kindle_clippings, letting you structure academic or personal notes alongside your professional contacts.
Real-World Use Cases
The Quarterly CRM Cleanup
An Ops Manager receives a massive vCard file from an old client system. Instead of spending hours manually copying names and job titles into a spreadsheet, they ask their agent to run the vcard-contacts-parser. The agent returns clean JSON immediately, ready for bulk import.
The Conference Debrief
A Sales Rep collects dozens of business cards and emails them into a single vCard file. They then use the parser to quickly filter out everyone who doesn't work in their target industry, letting them focus only on qualified leads.
Organizing Academic Notes
A student finishes reading a textbook and exports all highlights from Kindle into 'My Clippings.txt'. They run the parse_kindle_clippings tool, which automatically groups every highlight and note by the book title it came from.
Identifying Team Members
A project lead needs to know who on the team works at a specific company. They ask their agent: 'Find all contacts working at Acme Corp.' The parser scans the vCard and spits out only those names and titles.
The Tradeoffs
Sending raw .vcf files to general LLMs
Pasting a giant, unparsed address book export directly into Claude or Cursor. The model gets bogged down by binary data and hits context limits.
→ Use the vCard Contacts Parser MCP Server first. Let the parser strip the noise locally, then feed the resulting clean JSON to your AI client for analysis.
Trying to manually extract emails
Opening a 5,000-contact vCard file in Excel and trying to copy/paste all the email addresses into a new column. It's slow and error-prone.
→
Ask your agent to run the parser against the .vcf. Then prompt it: 'Extract only the emails and put them in CSV format.' Done.
Misunderstanding file scope
Thinking that running parse_kindle_clippings will help with a vCard export, because they are both data exports.
→
Remember the tools do different jobs. Use the VCF parser for address books (.vcf). Only use parse_kindle_clippings if you're dealing with Kindle notes.
When It Fits, When It Doesn't
Use this MCP Server if your data is in a messy, exported file format (like .vcf or raw text clippings) and needs to be put into strict JSON keys. It’s the essential first step for structured data ingestion.
Don't use it if: 1) You are already working within an application that provides clean APIs (e.g., a modern CRM with direct API access). In that case, connecting directly is better. 2) Your data source is highly complex or non-standard, like scanned PDFs requiring OCR—you’d need a different specialized tool for that.
This server excels at cleaning up common mobile/content exports so your agent can actually work with the data.
Common Questions About vCard Contacts Parser MCP
How does vCard Contacts Parser handle private contacts? +
It handles them by running 100% locally on your machine. Your personal phonebook never leaves your device, ensuring air-gapped privacy.
Can I use the vCard Contacts Parser for large groups of people? +
Yes. The parser is built to handle VCF files containing 5,000+ contacts without losing data or performance.
Is there another function besides parsing vCards? +
Yeah. It also includes the parse_kindle_clippings tool, letting you structure highlights and notes from Kindle exports into JSON format.
Does vCard Contacts Parser guarantee accurate phone numbers? +
Yes. Because it parses structured fields directly rather than interpreting raw text, the extraction of country codes and emails is highly precise; hallucination isn't a risk here.
How does vCard Contacts Parser ensure local privacy when reading my contact files? +
The parser runs 100% locally on your machine. Your personal phonebook never leaves your device; it processes and converts the raw data into JSON without needing to communicate with any external servers.
When running `vcard-contacts-parser`, how are multiple roles or phone numbers stored in the resulting JSON? +
It handles complex entries by structuring fields as arrays. Instead of overwriting a single field, it creates lists for phones and organizations, ensuring you get every number and title saved accurately.
How does `parse_kindle_clippings` process my Amazon Kindle highlights? +
It reads the raw text from your 'My Clippings.txt' file and structures it into JSON. This cleanly separates notes, bookmarks, and highlights, grouping them by the original book title for easy querying.
Is the `vcard-contacts-parser` compatible with various modern or legacy vCard formats? +
Yes. The parser is built to interpret the standard BEGIN:VCARD structure used by major platforms. It strips away non-standard binary noise, handling minor format variations effectively.
Is my address book uploaded to the cloud? +
Never. The vCard parsing is executed completely local on your device. Only the extracted text representation is provided to the AI context.
Does it support multiple contacts in a single file? +
Yes! It perfectly parses multi-vCard files exported from iOS, Google Contacts, or Android devices, handling thousands of entries seamlessly.
What happens to the contact profile pictures? +
Profile pictures (PHOTO;ENCODING=b) are intentionally ignored and stripped during parsing to preserve AI context tokens and prevent crashes.
Use it with your favorite AI tools
Connect this server to Cursor, Claude, VS Code, and more.