Compatible with every major AI agent and IDE
What is the vCard Contacts Parser MCP Server?
When you export your phone's address book, you get a massive .vcf file containing hundreds of contacts formatted in the legacy BEGIN:VCARD structure, often bloated with base64-encoded profile pictures. If you ask an LLM to read this raw file, it will exhaust its context window and hallucinate phone numbers and emails.
This MCP is a dedicated contact intelligence engine. It runs 100% local on your machine, instantly stripping away the binary noise and converting the raw vCard format into a beautiful, easily queryable JSON array. The AI sees exactly what it needs: First Name, Last Name, Organization, Phone, and Email.
The Superpowers
- 100% Air-Gapped Privacy: Your personal phonebook never leaves your local machine.
- Zero Hallucination: Perfect extraction of country codes, emails, and company roles.
- Massive File Support: Can instantly process a VCF file containing 5,000+ contacts.
- Assistant Ready: Ask your AI: 'Find the phone number for the CTO of Vinkius in my contacts.'
Built-in capabilities (1)
Paste the raw text content from the "My Clippings.txt" file found on a Kindle device. Parse Amazon Kindle "My Clippings.txt" exports into structured JSON. Extracts highlights, notes, and bookmarks grouped by book
Why LlamaIndex?
LlamaIndex agents combine vCard Contacts Parser tool responses with indexed documents for comprehensive, grounded answers. Connect 1 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
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Data-first architecture: LlamaIndex agents combine vCard Contacts Parser tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain vCard Contacts Parser tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query vCard Contacts Parser, a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what vCard Contacts Parser tools were called, what data was returned, and how it influenced the final answer
vCard Contacts Parser in LlamaIndex
vCard Contacts Parser and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect vCard Contacts Parser to LlamaIndex through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for vCard Contacts Parser in LlamaIndex
The vCard Contacts Parser MCP Server runs on Vinkius-managed infrastructure inside AWS — a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts. All 1 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in LlamaIndex only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
How Vinkius secures
vCard Contacts Parser for LlamaIndex
Every tool call from LlamaIndex to the vCard Contacts Parser MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
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.
How does LlamaIndex connect to MCP servers?
Use the MCP client adapter to create a connection. LlamaIndex discovers all tools and wraps them as query engine tools compatible with any LlamaIndex agent.
Can I combine MCP tools with vector stores?
Yes. LlamaIndex agents can query vCard Contacts Parser tools and vector store indexes in the same turn, combining real-time and embedded data for grounded responses.
Does LlamaIndex support async MCP calls?
Yes. LlamaIndex's async agent framework supports concurrent MCP tool calls for high-throughput data processing pipelines.
BasicMCPClient not found
Install: pip install llama-index-tools-mcp
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