Verified Burst

Verified Burst

MCP stdio server, one tool buy_verified_burst — x402 pay-only-if-verified inference.

Category
Visit Server

README

verified-burst broker

Sell verified inference bursts on Cerebras. An agent hits a hard / irreversible / low-confidence decision and buys more thinking: escalate to fast silicon → best-of-N → verify → pay per burst over x402, charged only if the answer passes. Budget-capped per agent.

BYOK passthrough: the customer's tokens are billed to their own Cerebras key — we never mark up tokens. We charge a small service fee for routing + verification + the burst guarantee. (Legal-clean: selling our application, not reselling their API.)

The wedge — one line for an agent builder

{ "mcpServers": { "verified-burst": {
    "command": "python3", "args": ["/root/inference-burst/mcp_server.py"] } } }

Their agent gains one tool, buy_verified_burst(request, strategy, n, verifier, answer_key), that returns a verified answer + receipt and bills per burst.

Files

file role
provider.py BYOK Cerebras call (OpenAI-compatible). Key never stored/logged.
burst.py verified-burst core: best-of-N + self-consistency / deterministic-check / judge verifiers. passed gates settlement.
pricing.py service-fee quote (not a token markup).
x402_gate.py x402 challenge + facilitator verify/settle. Settle only on passed = pay-only-if-verified. SIM until X402_FACILITATOR_URL set.
broker.py orchestration: quote → authorize → burst → settle-IF-verified, + per-agent budget cap.
server.py HTTP surface (POST /v1/burst, GET /v1/quote, /healthz).
mcp_server.py MCP stdio surface — the one-liner.
measure.py the 1-day BYOK measurement harness (offline + live).

Run

# offline measurement / shape
python3 measure.py --offline
# live (needs .env with CEREBRAS_API_KEY)
python3 measure.py
# HTTP broker
PORT=8402 python3 server.py
# MCP server is launched by the MCP client via the config above

Config (.env, gitignored)

CEREBRAS_API_KEY=csk-...        # required (BYOK)
CEREBRAS_MODEL=gpt-oss-120b     # this account: gpt-oss-120b | zai-glm-4.7 (NOT llama)
# x402 (REAL mode — omit for SIM):
X402_FACILITATOR_URL=...        # facilitator that verifies/settles payments
X402_PAY_TO=0x...               # seller wallet that receives USDC
X402_USDC_ASSET=0x...           # USDC contract on the chosen network
X402_NETWORK=base-sepolia

Go-live checklist

  • [ ] x402 creds: facilitator URL + seller wallet (X402_PAY_TO) + USDC asset. Until set, payments run in SIM (flow is real, settlement is stubbed).
  • [ ] Verify pricing: gpt-oss-120b per-token rate (current placeholder is UNVERIFIED) and set FEES in pricing.py to a margin you've checked.
  • [ ] Pick the verifier per use case: self_consistency (cheap, default), judge (adversarial, costs an extra call), or a caller deterministic_check (gold standard).
  • [ ] Budget cap: broker.DEFAULT_BUDGET_USD — wire to the AgentsPrice margin governor for real per-agent caps.
  • [ ] Cerebras gotcha: requests need a browser-ish User-Agent or Cloudflare returns 403 error 1010 (already handled).

Status (2026-06-15)

Core + both surfaces run live against real Cerebras. Verified→charged, failed→not charged, no-payment→402, budget-cap→refused — all confirmed. x402 in SIM pending creds.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured