AI Development
MCP Server Development
We build MCP servers that expose your systems as safe, well-defined tools for AI clients. Expect strict schemas, RBAC, audit logs, and deployment hardening so agents can act without dangerous access or data leakage. Delivery aligned to United States teams (USD).
Overview
What this service is
MCP (Model Context Protocol) is a way to expose tools and data sources to AI clients in a structured, consistent format.
We build MCP servers that wrap your internal APIs, databases, and services with strict schemas, permission checks, and audit logs.
Delivery includes deployment hardening and handoff notes so the tool surface stays safe as it grows.
Start Small
Start small in 7 days
Three pilot-friendly options that reduce risk and ship value fast. Choose one, share access, and we deliver a production-ready baseline.
Standard
AI delivery standard
Quality and safety practices we ship with AI builds so the system stays measurable, maintainable, and production-ready.
Logging + tracing
Conversation and tool traces with request IDs, error visibility, and debug-friendly runbooks.
Guardrails + safety
Tool allowlists, PII-safe patterns, refusal behavior, and escalation routes for edge cases.
Evals + regression tests
Golden queries, scorecards, and regression checks so quality improves over time instead of drifting.
Cost + latency controls
Caching, prompt discipline, retrieval tuning, and routing so your app stays fast and predictable at scale.
Documentation + handoff
Architecture notes, environment setup, and next-step roadmap so your team can iterate safely after launch.
Security-first integration
Secrets isolation, role-based access, audit-friendly actions, and minimal data retention by design.
Benefits
What you get
Expose tools safely for agent workflows
Reduce one-off integrations with standard interfaces
Keep permissions consistent via RBAC and policies
Improve auditability with logs and traceability
Ship tools faster with reusable schemas
Reduce risk of unsafe actions and leakage
Features
What we deliver
Tool schema design
Define tool contracts with stable schemas, validation, and versioning so clients can rely on predictable behavior.
RBAC and permission checks
Role-aware access controls so tool actions and data reads follow your existing security model.
Safe execution + validation
Parameter validation, allowlists, and approval patterns for sensitive actions.
Audit logs + tracing
Traceable tool usage with logs for debugging, compliance, and incident response.
Secrets and environment isolation
Safe secrets management and environment separation so tools don’t leak credentials or cross boundaries.
Deployment hardening
Rate limits, network controls, monitoring, and rollout discipline for production MCP deployments.
Process
How we work
Discovery
Tool inventory and permission model.
Schema design
Contracts, validation, and versioning plan.
Build
Implement MCP server + connectors.
Hardening
Rate limits, logs, and monitoring.
Launch
Rollout + handoff.
Tech Stack
Technologies we use
Core
Tools
Services
Use Cases
Who this is for
Internal tools as agent actions
Expose business APIs as safe tools for AI agents with permission enforcement and audit trails.
Ops automation tool surface
Wrap operational workflows (refunds, updates, approvals) as constrained tools with validation and approvals.
Data access with safety boundaries
Expose read-only or filtered queries to AI clients while preventing leakage across roles or tenants.
Multi-tool orchestration
Provide a clean tool catalog for AI workflow orchestration across systems.
Enterprise rollout readiness
Add governance, logs, and deployment controls for scalable adoption across teams.
AI Case Examples
Micro case studies (anonymous)
A few safe examples of outcomes we build for real operations—no client names, just results.
Secure Mobile Solution in Australian Defence Ecosystem
Problem: Secure data workflows were required in a regulated environment with strict access controls.
Solution: Hardened architecture with strict auth, encrypted storage, and audit-friendly engineering patterns.
Outcome: Deployed securely within a regulated ecosystem with clear handoff and operational guidance.
AI Knowledge Base Across 2,000+ Pages
Problem: Teams needed fast answers across long PDFs, but search was slow and results were inconsistent.
Solution: RAG with hybrid retrieval and reranking, plus grounded answers and safer fallback behavior.
Outcome: Reliable answers with <10s response times and measurable improvements on real queries.
Ops Automation with AI + n8n
Problem: Manual approvals and CRM syncing created delays and data inconsistencies across tools.
Solution: Event-driven automation with validation gates and AI-assisted classification where it improved routing.
Outcome: Reduced manual workload significantly with more reliable workflows and operator visibility.
Explore
Related solutions & technologies
Useful next pages if you’re planning an AI pilot or scaling this into a larger product.
Related solutions
FAQ
Frequently asked questions
APIs are great, but MCP provides a structured tool interface designed for AI clients. We often wrap APIs into MCP tools with better schemas, permissions, and observability.
Yes. Many MCP deployments start read-only, then expand to controlled actions with approvals as confidence grows.
We use allowlists, strict validation, RBAC, approvals, and audit logs—plus eval tests for common failure cases.
Yes. We implement rate limits, secrets isolation, network controls, and monitoring for production posture.
Yes. We deliver tool catalogs, schemas, and runbooks for safe maintenance and extension.
Start with the highest-value read actions (search, lookups) and one controlled write action with approvals.
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Regional
Delivery considerations for your region
Compliance & Data (US)
For US teams, we build with auditability in mind: clear access boundaries, least-privilege roles, and reviewable operational controls.
We can align delivery with SOC 2 / ISO-friendly practices (without claiming certification): evidence-ready logs, secure-by-default config, and clear ownership.
- SOC 2 / ISO-friendly implementation patterns (no certification claims)
- Least-privilege access and permission boundaries
- Security review checklists for auth, payments, and data flows
- PII-safe logging + incident response playbooks (on request)
- Retention and deletion flows where required
- NDA + vendor onboarding docs on request
Timezone & Collaboration (Americas)
We support teams across the Americas with meeting windows that work for EST/CST/MST/PST.
We keep delivery predictable with weekly milestones, concise async updates, and written decisions to reduce calendar load.
- Americas overlap with EST/PST-friendly windows
- Async-first updates with written decisions
- Weekly milestone demos + change control
- Fast turnaround on blockers and clarifications
- Clear owner per workstream and escalation path
Engagement & Procurement (US)
US-friendly engagement structure: clear SOWs, milestone billing, and invoice cadence that fits typical procurement workflows.
If you need vendor onboarding artefacts, we can provide security posture summaries and delivery process documentation.
- USD invoicing and milestone-based payment schedules
- SOW + scope lock options for fixed-scope work
- Time-and-materials for evolving requirements
- Procurement-ready documentation on request
- Optional paid discovery to de-risk delivery
Security & Quality (US)
We ship with a security-first checklist and performance budgets—so releases stay stable under real traffic.
Expect clean PRs, reviewable changes, and production-ready testing from day one.
- Threat-aware checks for auth, roles, and sensitive data flows
- CI-friendly testing: unit + integration + critical path smoke tests
- Performance budgets (Core Web Vitals-minded) and bundle checks
- Structured logging + error tracking hooks (Sentry-ready)
- Rollback-safe releases and clear release notes
Want help with MCP server development?
Share your requirements for United States delivery. USD-based engagements.
Reply within 2 hours. No-pressure consultation.