Model Context Protocol Experts in Frankfurt
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Meet FRATCH Experts in Frankfurt, who have recently used Model Context Protocol
Ali Aminian
Last position:
Platform Engineer & Software Architect at Yatta GmbH
- Architected the Yatta Integration Layer – a config-driven integration platform on Java 25, Spring Boot 4 (WebFlux), Temporal, gRPC and Kafka, enabling new third-party integrations (e.g. AVS fulfillment) via declarative JSON configs with zero code changes.
- Designed and implemented Tink integration with 0Auth IBAN verification to enhance fraud prevention and account validation workflows with Adyen payByBank.
- Architected and implemented an OpenFGA-based authorization model for centralized management of users, groups, and fine-grained access control in the vendor portal.
- Architected and led delivery of the Yatta API Gateway platform using GraphQL Federation, providing a unified enterprise API layer across distributed microservices with centralized authentication, authorization and request orchestration.
- Replaced NGINX + NLB with Istio service mesh and AWS ALB; rolled out WAF, OAuth (Cognito), IP whitelisting and RBAC across environments.
- Migrated CDC from Confluent Cloud connectors to a self-hosted Kafka Connect + Debezium stack, reducing operational cost by ~80% across multiple environments.
- Implemented the Transactional Outbox pattern with Debezium for reliable, exactly-once event publishing to Kafka with Avro and Schema Registry.
- Migrated dunning/payment-recovery workflows from Airflow to Temporal, achieving 99.9% reliability for settlement handling.
- Optimised Apache Airflow with deferrable sensors to handle 1000+ concurrent DAG runs without scaling the worker pool.
- Refactored a monolithic Terraform codebase into 3 modular projects, cutting deployment time by ~45%.
- Stood up full observability with OpenTelemetry, Tempo, Prometheus and Loki; automated dev/staging/prod with ArgoCD, Image Updater and Helm.
- Collaborated with product, operations and engineering stakeholders to define scalable platform architecture and integration standards aligned with long-term business and operational goals.
Saqib Javed
Last position:
AI Developer / AI Engineer (Lead) at KOM4TEC GmbH
- Conceptual design and implementation of modular AI assistants for sales and business processes in the Microsoft ecosystem (Agentic AI, Copilot extensions)
- Frontend architecture and development with React + TypeScript for embedded chat and assistant surfaces (streaming UI, hooks, React Query, OpenAPI clients)
- Enterprise-level agent development: reusable skill/agent library, MCP server, review and compliance gates
- LLM integration into the user experience: Anthropic (Claude), OpenAI, tool use, RAG pipelines, prompt engineering, guardrails
- Architecture and code review consulting as well as mentoring in the AI development team
- Integration with Microsoft Graph, Power Platform, and Azure services
- Technologies: React, TypeScript, Anthropic Claude, OpenAI, MCP, RAG, Microsoft Graph, Power Platform, Azure
Noel Lang
Last position:
Founder & Lead Engineer at ausbildung-in-der-it.de
- Platform established and running stably; deliberately reducing my involvement to refocus on an engineering mandate in the financial sector.
- Built an own SaaS learning platform from the ground up and scaled it to over 20,000 users (over 6,000 courses sold, B2C and B2B); end-to-end ownership from development through infrastructure to operations.
- Built a lab environment that provisions an isolated Linux container per user (Docker, Traefik, Go), including automatic provisioning and a dedicated subdomain per user.
- Integrated LLM features into the product and accelerated development end-to-end with AI-assisted workflows (Claude Code, Codex); CI/CD with automated tests.
Markus Kollers
Last position:
Founder & Managing Director at Qrafto UG (haftungsbeschränkt)
- Founding and overall responsibility: Built a B2B SaaS platform for craft and construction businesses from the first line of code to the live launch with the first paying customer; solo founding including full establishment of the company and all business processes.
- Product and technology responsibility: Designed and developed the entire product.
- Infrastructure & DevOps: Managed a Kubernetes/Helm environment including CI/CD, monitoring, and security architecture; GDPR-compliant platform decisions and evaluation of EU-hosted LLM providers.
- Agentic coding as a productivity multiplier: Set up a productive multi-agent environment with Claude Code: up to eight parallel agents in isolated Git worktrees, Telegram-based remote control and monitoring, MCP integrations (e.g., Context7, Playwright for E2E tests), and a builder-critic pattern with custom slash commands (/research, /plan) and compressed project contexts. Result: development throughput on par with a small team while working solo.
- Go-to-market: Independently developed positioning, SEO and direct mail playbook, as well as target group analysis.
- Regulation & finance: Implemented e-invoicing requirements (ZUGFeRD/XRechnung), set up accounting and payment infrastructure, and managed funding and financing options.
Alona Liuzniak
Last position:
AI Architect
AI-powered platform for automated UX validation and designer support
- Designed and led technical implementation of an enterprise-wide AI solution for automated UX review that improved design quality and significantly reduced manual review processes in teams
- Developed an automated UX validation tool as a Figma plugin and web application that generates test cases based on internal guidelines and reliably checks current designs for consistency and standard compliance
- Implemented an interactive designer chat based on RAG that answers questions about the current design and the company's UX guidelines, and designed the deployment architecture using containerized services
- Python, Azure OpenAI, PostgreSQL, REST API, Docker, OpenShift, Helm, CI/CD, Figma MCP, LLM, RAG, Prompt Engineering, GenAI, XAI, AI Architecture, AI Strategy
Jochen Hinrichsen
Last position:
DevSecOps Expert at DB InfraGO
- Central build and delivery for 20+ applications, 100+ pipelines/day, 700+ GitLab projects
- Build pipelines for Go, Java and JavaScript
- Provisioning of 100+ components
- Quality assurance via GitLab Code Quality and SonarQube
- Checks for dependencies, licensing and vulnerabilities
- Release creation via Jira and ServiceNow
- SBOM, Supply Chain Security, distroless images
- PoC GitLab Runner: Nomad vs. Kubernetes
- Technologies: Artifactory, buildah, GitLab Premium, Go, Gradle, Jenkins, Mend, Podman
Discover over 15,000 top freelancers
Statistics of experts using Model Context Protocol
Aggregated from the professional profiles of matched freelancers.
Experience
18 years (Germany: 17 years)
Position duration
2.2 years (Germany: 2 years)
Positions per freelancer
11
Top business areas
Information Technology, Product Development, Project Management
Top industries
Information Technology, Banking and Finance, Education
Certification focus areas
Information Technology, Business Intelligence, Legal
Bachelor's degree or higher
100% (Germany: 96%)
Master's degree or higher
17% (Germany: 65%)
Certifications per freelancer
3
Most common languages
German, English, French
Speak two or more languages
100% (Germany: 97%)
Based on our profile pool as of 30 Aug 2026.
Daily rate distribution
The chart shows how the daily rates of freelancers in this technology in Frankfurt are distributed, based on recent contracts on our platform. Each bar covers a rate range — its height shows how many freelancers charge within that range.
Average rates of experts in Frankfurt using Model Context Protocol
Rates are based on recent contracts and do not include FRATCH margin.
The average daily rate is the mean of all daily rates from recent contracts of comparable freelancers on our platform.
The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 30 Aug 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
About the technology
What MCP is
Model Context Protocol, often called MCP, is a standard for connecting AI assistants to external tools, data, and services in a controlled way. It helps model clients discover what is available, request actions, and read context without custom one-off integrations for every system.
Common use cases
- Expose internal documents, tickets, or knowledge bases to AI assistants
- Connect agents to APIs, databases, and workflow tools
- Build MCP servers for internal platforms and product features
- Standardize access across multiple model clients and agent apps
Ecosystem and tooling
Strong specialists work with MCP servers and clients, transport options, schemas, and auth flows. They also understand how MCP fits with LLM apps, tool calling, observability, and existing APIs. In Frankfurt, this often matters for teams that need secure integration across regulated and multilingual environments.
When companies bring in help
Companies usually look for freelance expertise when they need a clean first implementation, a review of an existing MCP setup, or help turning a proof of concept into something stable. They also bring in specialists when internal teams need guidance on security, versioning, and how MCP should sit next to current API layers.
What strong professionals do
Good MCP professionals think in contracts, not demos. They define clear tool boundaries, handle context size carefully, and make sure prompts, permissions, and failures behave predictably. They also write documentation that other specialists can maintain without guesswork.
How to judge quality
Look for people who can explain the protocol in plain language and show how they tested it end to end. Strong work includes clean server design, safe access to data, and a realistic view of where MCP helps and where a direct integration is still better.
Frequently asked questions
Quick answers to the questions that come up most around Model Context Protocol.
Model Context Protocol is used to connect AI assistants to tools, data sources, and actions through a shared interface. It is useful when you want one assistant to work across documents, systems, and workflows without building a separate integration for each one.
MCP is the common short form for Model Context Protocol, and many people first saw it in Anthropic-related materials. Today it is used more broadly as an open protocol for tool and context connections, not just for one model provider.
A strong Model Context Protocol specialist helps when you are moving from a prototype to a real integration. That usually means designing an MCP server, connecting existing APIs, or reviewing how tools and permissions should work before wider release.
Model Context Protocol gives teams a more consistent way to expose tools and context than ad hoc tool calling in each app. Custom integrations can still be fine for simple cases, but MCP is stronger when multiple assistants or clients need the same capabilities.
A good MCP specialist usually also knows API design, JSON schemas, authentication, and secure handling of internal data. Experience with LLM apps, observability, and backend services helps when the protocol needs to fit into an existing system.
A Model Context Protocol proof of concept can be small, but production work needs someone who understands reliability, access control, and maintainability. If the project touches sensitive data or multiple internal systems, you want more than a quick setup.
Yes, most MCP work can be done remotely because the core tasks are design, integration, and testing. For Frankfurt teams, hybrid collaboration can still help during security reviews, architecture sessions, or when a specialist needs access to local systems.
A strong Model Context Protocol freelancer should explain the protocol clearly, show working examples, and describe how they handled errors and permissions. Look for clean server structure, sensible tool naming, and documentation that lets other specialists continue the work.
The average hourly rate of freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects is 104 €, which corresponds to a daily rate of about 831 € based on an 8-hour working day.
Of the freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects, 100% hold at least a Bachelor's degree and 17% hold at least a Master's degree.
On average, freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects have 18 years of professional experience, with a single engagement typically lasting around 2.2 years.
The most common languages among freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects are German (100%), English (100%), and French (33%).
The most common industries among freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects are Information Technology (100%), Banking and Finance (83%), and Education (50%).
The most common business areas among freelancers in Frankfurt, Germany who have used Model Context Protocol in their recent projects are Information Technology (100%), Product Development (100%), and Project Management (67%).
Main locations of FRATCH Experts, who have recently used Model Context Protocol
Our freelancers and interim experts are at home across the DACH region — available on-site in the major business hubs or fully remote. Choose a location to discover matched specialists, local market insights and up-to-date availability.
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Munich Request a free demo
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Philipp Thomaschewski
FRATCH CEO
