Bring Fauna
to LlamaIndex
Learn how to connect Fauna (Serverless DB) to LlamaIndex and start using 1 AI agent tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the Fauna (Serverless DB) MCP Server?
Connect your Fauna serverless database to any AI agent and manage your data infrastructure through natural conversation and powerful FQL queries.
What you can do
- Execute FQL — Run any Fauna Query Language (FQL) command to read, create, update, or delete data across your database.
- Data Exploration — List collections, query indexes, and fetch specific documents directly from your AI interface.
- Parameterized Queries — Use the arguments field to pass complex JSON data safely into your FQL execution logic.
- Schema Management — Inspect and manage your database schema, including collections and indexes, using standard FQL commands.
How it works
- Subscribe to this server
- Enter your Fauna Secret (and optional Region URL)
- Start managing your serverless data from Claude, Cursor, or any MCP-compatible client
No more switching to the Fauna dashboard for quick data lookups or schema checks. Your AI acts as a database administrator and developer assistant.
Who is this for?
- Backend Developers — test FQL queries and verify data state directly from the code editor.
- Data Engineers — perform quick data migrations or cleanup tasks using natural language prompts.
- Product Teams — retrieve real-time usage metrics or user data without needing a custom admin panel.
Built-in capabilities (1)
Can be used for reading, creating, updating, or deleting data depending on the FQL string provided. Execute a Fauna Query Language (FQL) query
Why LlamaIndex?
LlamaIndex agents combine Fauna (Serverless DB) 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 Fauna (Serverless DB) tool responses with indexed documents for comprehensive, grounded answers
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Query pipeline framework lets you chain Fauna (Serverless DB) tool calls with transformations, filters, and re-rankers in a typed pipeline
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Multi-source reasoning: agents can query Fauna (Serverless DB), a vector store, and a SQL database in a single turn and synthesize results
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Observability integrations show exactly what Fauna (Serverless DB) tools were called, what data was returned, and how it influenced the final answer
Fauna (Serverless DB) in LlamaIndex
Fauna (Serverless DB) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Fauna (Serverless DB) 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 Fauna (Serverless DB) in LlamaIndex
The Fauna (Serverless DB) 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
Fauna (Serverless DB) for LlamaIndex
Every tool call from LlamaIndex to the Fauna (Serverless DB) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I perform write operations like creating or updating documents?
Yes. The execute_fql tool allows any valid FQL command. If your Fauna Secret has the appropriate permissions (e.g., 'server' or 'admin' role), you can create, update, and delete data.
How do I handle complex query arguments?
You can use the optional arguments parameter in the execute_fql tool. Pass a JSON object containing your variables, and reference them within your FQL string.
Does this support Fauna's regional endpoints?
Yes. You can provide a FAUNA_REGION_URL (e.g., for US or EU regions) as an optional credential during setup to ensure the agent connects to the correct database cluster.
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 Fauna (Serverless DB) 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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