Fireworks AI Inference MCP Server
MCP server for Fireworks AI — a fast LLM inference platform supporting hundreds of open-weight models including Llama, Mixtral, Qwen, DeepSeek, and custom fine-tuned models. Enables AI agents to call open-weight models with competitive pricing, fast inference, and the ability to deploy custom fine-tuned models.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
AI inference platform. SOC2. US-only. Custom model deployment. API key and prompt injection protection required.
⚡ Reliability
Best When
An agent developer needs fast, cheap inference on open-weight models with the option to deploy custom fine-tunes — building production agents without proprietary model lock-in.
Avoid When
You need GPT-4, Claude, or Gemini — Fireworks only serves open-weight models. FINANCIAL RISK: Agent chains with multiple LLM calls can accumulate inference costs.
Use Cases
- • Fast open-weight model inference from agent development and production workflows
- • Deploying custom fine-tuned models via Fireworks for domain-specific agent tasks
- • High-throughput batch inference from data processing pipeline agents
- • Testing multiple open-weight models (Llama, Mixtral, Qwen) for agent selection
Not For
- • Proprietary model access (Fireworks serves open-weight models only)
- • Multimodal video tasks at scale (primarily text/image)
- • Non-ML inference tasks
Interface
Authentication
Fireworks API key authentication. OpenAI-compatible API format. Keys managed in Fireworks console.
Pricing
Pay-as-you-go pricing. Very competitive for high-volume open-weight model inference. Custom model deployment has additional costs.
Agent Metadata
Known Gotchas
- ⚠ FINANCIAL RISK: Agent chains with repeated LLM calls accumulate inference costs
- ⚠ Open-weight models only — no proprietary frontier models
- ⚠ Custom model deployment has additional billing complexity
- ⚠ US-only data processing — not for EU data residency requirements
- ⚠ OpenAI-compatible API but verify function calling compatibility per model
Alternatives
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Scores are editorial opinions as of 2026-03-07.