Quesen MCP Server

Quesen — Developer Portal

Quesen is the deterministic AI decision engine for A2A (Agent-to-Agent) risk evaluation. It is the trust filter that sits between autonomous agents and capital loss.

This repository is the public developer portal. It contains only documentation, integration guides, examples, registry manifests, and reference links. No engine source code lives here. Quesen's engine implementation is sovereign, non-public infrastructure.

Live production

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Quick start (30 seconds)

Python

pip install quesen-sdk

from quesen_sdk import QuesenClient

q = QuesenClient(base_url="https://web-production-30ab5.up.railway.app",
                 api_key="YOUR_KEY")

verdict = q.validate(domain_age_days=1, engagement_ratio=0.95, scam_keyword_count=4)
if verdict.decision == "SKIP":
    return  # respect the deterministic answer

JavaScript / TypeScript

npm i quesen-sdk

import { QuesenClient } from "quesen-sdk";

const q = new QuesenClient({
  baseUrl: "https://web-production-30ab5.up.railway.app",
  apiKey: process.env.QUESEN_API_KEY,
});

const verdict = await q.validate({
  domain_age_days: 1,
  engagement_ratio: 0.95,
  scam_keyword_count: 4,
});

Framework wrappers

MCP (Claude Desktop, Cursor, Windsurf, etc.)

Quesen exposes five MCP tools over the production endpoint. See docs/mcp.md for the client-config snippet.

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Why Quesen?

Autonomous agents make more decisions per second than any human oversight can audit. When those decisions involve capital — launching a token, opening a position, executing a trade, greenlighting a smart-contract deployment — the marginal cost of a bad decision is fatal.

Quesen answers exactly one question:

Should the calling agent proceed with this action?

Inputs are typed. Outputs are one of PROCEED, REVIEW, SKIP, always with a risk_score in [0.0, 1.0], a confidence in [0.0, 1.0], and the exact conflict rules that fired. Same inputs → same output. Every time. Every response embeds engine_version, weights, and thresholds. Fully reproducible. Fully auditable.

What Quesen is not

• Not an LLM wrapper. No prompts. No probabilities.
• Not a chatbot. It is A2A infrastructure.
• Not a KYC/identity system. It scores risk, not identity.
• Not chain-locked / framework-locked / LLM-locked. Ecosystem-neutral by design.

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Documentation

• Architecture overview
• Integration guide
• API reference
• MCP setup
• Pricing tiers
• FAQ
• Registry status

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Live status

• Production: https://web-production-30ab5.up.railway.app
• Health check: GET /health returns {"status":"ok","engine_version":"1.9.0"}
• Version snapshot: GET /version returns full engine + billing + on-chain flags (ASP/1.0)
• Uptime and version widget on senueren.co.za/quesen

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Registry presence

Quesen is discoverable via Model Context Protocol registries and the standard agent-directory ecosystem. See docs/registries.md for the current state of each submission. Manifests:

• smithery.yaml — Smithery.ai (canonical)
• mcp.json — MCP.so / generic MCP client (canonical)
• .well-known/ai-plugin.json — OpenAI plugin manifest / .well-known/ai-plugin.json autodiscovery
• llms.txt — machine-readable summary for LLM crawlers

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Contributing

This is a documentation-only repository. Engine PRs cannot be accepted here. If you have integration-specific feedback, please open an issue or read CONTRIBUTING.md.

SDK contributions belong in the corresponding public SDK repository:

• Python: Shxnque/quesen-sdk-py
• JavaScript: Shxnque/quesen-sdk-js
• LangChain: Shxnque/quesen-langchain
• CrewAI: Shxnque/quesen-crewai
• AutoGen: Shxnque/quesen-autogen

Security issues: please read SECURITY.md before filing publicly.

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License

MIT. See LICENSE.