Bring Llm Inference
to LlamaIndex
Learn how to connect Cerebras Inference to LlamaIndex and start using 15 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 Cerebras Inference MCP Server?
Connect to the Cerebras Inference platform to leverage the world's fastest AI inference. This MCP server allows your AI agent to interact with state-of-the-art models like Llama 3.1 and others using the Cerebras Wafer-Scale Engine (WSE) for unprecedented performance.
What you can do
- Chat & Text Completions — Generate high-speed responses using
create_chat_completionandcreate_completionwith support for streaming and tool calling. - Model Discovery — Explore available models and their specific details using
list_modelsandget_modelto choose the best fit for your task. - Batch Processing — Handle large-scale workloads asynchronously with
create_batch,list_batches, andcancel_batchfor efficient data processing. - File Management — Upload and manage JSONL files for batch jobs using
upload_fileandlist_filesdirectly from your agent. - Performance Metrics — Monitor your usage and performance metrics to optimize your inference workflows.
How it works
- Subscribe to this server
- Enter your Cerebras API Key
- Start generating tokens at speeds you've never seen before in Claude, Cursor, or any MCP-compatible client.
Who is this for?
- AI Developers — build and test applications with near-instant model responses to maintain development momentum.
- Data Scientists — run large-scale batch inference on massive datasets using the asynchronous batch API.
- Product Teams — integrate high-performance LLMs into production environments where latency is a critical factor.
Built-in capabilities (15)
Cancel a batch job
Create a batch job for asynchronous processing
Generate conversational responses using a structured message format
Generate text continuations from a single prompt string
Delete a file
Retrieve status of a batch job
Retrieve metadata for a specific file
Download raw content of a file
Retrieve Prometheus-formatted operational metrics
Fetches details for a specific model
List all batch jobs
List uploaded files
Lists all currently available models
Retrieve model details without an API key
Upload a JSONL file for Batch processing
Why LlamaIndex?
LlamaIndex agents combine Cerebras Inference tool responses with indexed documents for comprehensive, grounded answers. Connect 15 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.
- —
Data-first architecture: LlamaIndex agents combine Cerebras Inference tool responses with indexed documents for comprehensive, grounded answers
- —
Query pipeline framework lets you chain Cerebras Inference tool calls with transformations, filters, and re-rankers in a typed pipeline
- —
Multi-source reasoning: agents can query Cerebras Inference, a vector store, and a SQL database in a single turn and synthesize results
- —
Observability integrations show exactly what Cerebras Inference tools were called, what data was returned, and how it influenced the final answer
Cerebras Inference in LlamaIndex
Cerebras Inference and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Cerebras Inference 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 Cerebras Inference in LlamaIndex
The Cerebras Inference 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 15 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
Cerebras Inference for LlamaIndex
Every tool call from LlamaIndex to the Cerebras Inference MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
How do I check which models are available for inference?
Use the list_models tool. It will return a list of all supported models, including high-performance options like Llama 3.1, which you can then use in create_chat_completion.
Can I process thousands of requests at once?
Yes. Use upload_file to provide your JSONL data and then create_batch to start an asynchronous processing job. You can monitor progress with get_batch.
Does this server support tool calling and structured outputs?
Yes. The create_chat_completion tool supports tools, tool_choice, and response_format parameters, allowing the model to interact with other functions or return valid JSON.
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 Cerebras Inference 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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