You will get a custom production MCP server connecting Claude to your tools
Project details
I build production-grade MCP (Model Context Protocol) servers that let Claude — or any MCP-compatible AI agent — securely use your APIs, databases, and internal tools.
You get clean, typed, well-tested code (TypeScript or Python), proper error handling and input validation, clear setup docs, and a server that holds up in production — not a fragile demo.
Why me: I'm an audit-proven engineer (1st-place Solana security audit, 125+ vulnerabilities documented) who builds real agent systems. Reliability and security are the default — every tool validated, every failure path handled.
Typical builds: REST/GraphQL API wrappers, database query tools, SaaS integrations, on-chain/Web3 data access, internal automation. If your agent needs to talk to it, I can wrap it in MCP.
Fully async (Jakarta UTC+7), with written updates and a clean handoff.
You get clean, typed, well-tested code (TypeScript or Python), proper error handling and input validation, clear setup docs, and a server that holds up in production — not a fragile demo.
Why me: I'm an audit-proven engineer (1st-place Solana security audit, 125+ vulnerabilities documented) who builds real agent systems. Reliability and security are the default — every tool validated, every failure path handled.
Typical builds: REST/GraphQL API wrappers, database query tools, SaaS integrations, on-chain/Web3 data access, internal automation. If your agent needs to talk to it, I can wrap it in MCP.
Fully async (Jakarta UTC+7), with written updates and a clean handoff.
AI Algorithms
Large Language Model, Multimodal Large Language ModelAI Applications
Conversational AIAI Development Language
PythonAI Models
ChatGPT, GPT-4, LLaMAWhat's included
| Service Tiers |
Starter
$149
|
Standard
$499
|
Advanced
$999
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 2 | 5 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | |
Model Documentation | - | - | - |
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | - | - | - |
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | - | - | - |
Setup File | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Additional tool / endpoint
(+ 2 Days)
+$75Frequently asked questions
About Rheza
AI Agent Engineer on Solana | Audit-Proven | RECTOR LABS
Bekasi, Indonesia - 4:26 am local time
I don't build chatbots that get stuck. I build agentic systems that survive mainnet: LLMs that orchestrate real on-chain actions, agent privacy infrastructure, multi-chain stealth tooling. Every line of agent code I ship is audited like a smart contract — because that's what agents are: programs with money and autonomy.
What I build:
- Production agentic apps — LLM tool calling, multi-step reasoning, auto-recovery, preflight simulation
- Agent infrastructure on Solana — REST APIs + skill files for AI agents to consume on-chain primitives
- Solana programs — Rust + Anchor, audit-grade architecture, on-chain logic that survives mainnet
- Agent privacy — stealth addresses, viewing keys, Pedersen commitments across 17 chains
- Smart contract security — vulnerability hunting, audit reports, mitigations (13 findings across 14 audited Solana repos)
Proof of work:
- Sipher — Privacy-as-a-Skill for Multi-Chain Agents (66 endpoints, 17 chains, on-chain Anchor program, 1,402 tests, live in production)
- Kami — AI Co-Pilot for Kamino DeFi (plain English → signed mainnet tx, LLM auto-recovery, live on Solana mainnet)
- 11 hackathon & bounty wins — $36,050+ across the Solana ecosystem
- $10K Solana Foundation grant + $6K audit subsidy for SIP Protocol
- 1st of 116 in a Solana Security Audit — 13 findings across 14 repos, incl. a framework-level Anchor CPI bug (CVSS 7.5, fixed upstream)
How I work:
- Production-first — every line written as if it ships tonight, audited tomorrow
- Fully async — written updates + Loom walkthroughs by default. I'm in Jakarta (UTC+7); async keeps us both unblocked across time zones. Saves you status meetings, gives me deep focus.
- Honest comms — clear timelines, no scope creep, no ghosting
- Security-conscious — agents move money, so the bar is high
- Pragmatic — I ask questions before coding, pick the right tool, and say "no" when a feature doesn't serve the goal
Stack: Solana, Rust, Anchor, TypeScript, Next.js, Vercel AI SDK, MCP, Noir (ZK), Python, Docker, PostgreSQL
Let's ship a production agent — for your DeFi protocol, your trading desk, your DAO treasury, or whatever else needs to be smart, secure, and on-chain.
Steps for completing your project
After purchasing the project, send requirements so Rheza can start the project.
Delivery time starts when Rheza receives requirements from you.
Rheza works on your project following the steps below.
Revisions may occur after the delivery date.
Scope & spec
Confirm the tools, data sources, auth, and transport, then agree on the final tool list.
Build & test
Implement the MCP server, validate every tool, and add error handling and tests.